diff --git a/conf/ppo/config.yaml b/conf/ppo/config.yaml
index bebd8b8f8..5b6d63827 100644
--- a/conf/ppo/config.yaml
+++ b/conf/ppo/config.yaml
@@ -86,6 +86,12 @@ training:
   cam_tracking: false
   cam_tracking_env_idx: 0
   cam_tracking_extra_envs: 2
+  # MuJoCo geom groups to hide during offline play/video (0..5); e.g. OpenArm cell shell uses group 1.
+  play_hide_geom_groups: []
+  # MP4 playback fps; null = match physics (1/ctrl_dt). Lower = slower on-screen motion.
+  play_video_fps: null
+  # If true, play/export uses stochastic policy samples (more motion when the mean is near zero).
+  play_stochastic: false
   log_root: null
   num_timesteps: null
   log_dir: null
diff --git a/conf/ppo/task/openarm_demo_pick/mujoco.yaml b/conf/ppo/task/openarm_demo_pick/mujoco.yaml
new file mode 100644
index 000000000..f48ae8b48
--- /dev/null
+++ b/conf/ppo/task/openarm_demo_pick/mujoco.yaml
@@ -0,0 +1,63 @@
+# @package _global_
+# Base OpenArm demo pick task (MuJoCo). The cube pick/place bring-up on the vendored
+# ``demo.xml`` cell. Variants under this folder (e.g. mujoco_lift3d) override the scene,
+# reward shaping and goal for the 3D lift task.
+training:
+  task_name: OpenArmDemoPick
+  sim_backend: mujoco
+  no_play: true
+  render_spacing: 2.0
+  cam_distance: 2.75
+  cam_elevation: -30.0
+  cam_azimuth: 222.0
+  cam_lookat: [0.34, -0.02, 1.05]
+  # Hide only the cell enclosure mesh (group 3) so the work surface (sheet) and the
+  # lifter support block stay visible; the closed cabinet would otherwise occlude the arm.
+  play_hide_geom_groups: [3]
+  # 5 fps over 50 Hz physics = 10x slow motion, easier to inspect the grasp.
+  play_video_fps: 5
+  play_steps: 200
+algo:
+  num_envs: 4096
+  num_steps_per_env: 24
+  max_iterations: 1500
+  save_interval: 500
+  empirical_normalization: true
+  obs_groups:
+    actor: [policy]
+    critic: [policy]
+  policy:
+    init_noise_std: 1.0
+    actor_hidden_dims: [512, 256, 128]
+    critic_hidden_dims: [512, 256, 128]
+    activation: elu
+    class_name: ActorCritic
+  algorithm:
+    value_loss_coef: 1.0
+    clip_param: 0.2
+    entropy_coef: 0.01
+    num_learning_epochs: 4
+    num_mini_batches: 8
+    learning_rate: 0.0003
+    schedule: adaptive
+    gamma: 0.99
+    lam: 0.95
+    desired_kl: 0.015
+    max_grad_norm: 0.5
+env:
+  action_scale: 0.04
+  fix_lifter: true
+  left_arm_only: true
+  rigid_freeze_right_arm: true
+  binary_gripper: false
+  playback_hide_geom_groups: [3]
+  playback_video_fps: 5
+reward:
+  scales:
+    reach: 1.0
+    place: 0.8
+    lift: 0.35
+    grasp: 0.22
+    success: 25.0
+    action: -0.01
+    drop: -1.0
diff --git a/conf/ppo/task/openarm_demo_pick/mujoco_lift3d.yaml b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d.yaml
new file mode 100644
index 000000000..25628c547
--- /dev/null
+++ b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d.yaml
@@ -0,0 +1,45 @@
+# @package _global_
+# Lift line (hard, in-air goal). Builds on the base demo pick task with:
+#   * graspability-tuned scene (demo_lift3d.xml: 3cm cube, higher friction, no black_frame),
+#   * fingertip TCP reach (reach_use_tcp + reach_tcp_offset, the grasp-alignment fix),
+#   * 3D lift goal (goal_success_mode=lift3d) ~0.12 m above the spawn band,
+#   * binary gripper, and proximity-gated dense lift (lift_gate_mode=proximity)
+#     to escape the "jaws-on-cube, never lift" local optimum.
+defaults:
+  - /task/openarm_demo_pick/mujoco
+  - _self_
+env:
+  action_scale: 0.055
+  binary_gripper: true
+  scene:
+    model_file: src/unilab/assets/robots/openarm_mujoco_v2/demo_lift3d.xml
+  # In-air goal above the (narrowed) spawn band center: lift the cube ~0.12 m straight up.
+  goal_pos: [0.46, 0.0, 1.13]
+  cube_xy_range: [0.44, 0.48, -0.04, 0.04]
+reward:
+  scales:
+    reach: 1.0
+    place: 0.0
+    lift: 12.0
+    grasp: 0.6
+    success: 25.0
+    action: -0.01
+    drop: -1.0
+    lift_bonus: 10.0
+    goal_track_coarse: 16.0
+    goal_track_fine: 5.0
+  fall_z: 0.86
+  table_z: 1.008
+  lift_shaping_span: 0.12
+  grasp_proximity_decay: 6.0
+  place_use_grasp_gate: true
+  # Proximity-only soft gate on dense lift: robust to closure wobble, monotonic rest->goal gradient.
+  lift_gate_mode: proximity
+  lift_use_grasp_gate: true
+  reach_use_tcp: true
+  reach_tcp_offset: [-0.0025, 0.0, -0.0669]
+  goal_success_mode: lift3d
+  success_dist: 0.05
+  lift_margin: 0.05
+  goal_track_coarse_std: 0.1
+  goal_track_fine_std: 0.03
diff --git a/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip.yaml b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip.yaml
new file mode 100644
index 000000000..7b42dbced
--- /dev/null
+++ b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip.yaml
@@ -0,0 +1,48 @@
+# @package _global_
+# Continuous-gripper lift3d pick: policy-controlled (action_scale-limited) finger
+# closing instead of the binary snap-close, with staged + firm grasp shaping.
+#
+# Same task as mujoco_lift3d (3D in-air goal) but the gripper is closed
+# continuously by the policy, which is more physical but harder to learn. The
+# reward shaping below is what makes a deliberate, goal-accurate, sustained pick
+# emerge:
+#   * terminate_on_success=false: keep the episode alive after success so the
+#     continuous gripper is actually paid to *hold* the cube at the goal
+#     (hold_success / goal_track accrue per step); otherwise the cube slips right
+#     after the success latches.
+#   * grasp 0.4, drop -4.0, hold_success 8.0, goal_track_coarse 24.0: reward
+#     sustained closure x proximity and holding *at the goal*, punish drops, and
+#     pull hard toward the in-air goal to escape the "grab and hold low" optimum.
+#   * approach 1.0 / premature_close -0.5 / action_rate -0.02: staged-grasp
+#     terms -- a gentle nudge to go above the cube with the gripper open before
+#     closing, a mild penalty for closing far (xy) from the cube, and a
+#     smoothness penalty -- so the pick is segmented (above-open -> close ->
+#     lift) rather than a single swipe.
+#   * firm_grasp 8.0: closure x lift_gate x proximity, paid only once the cube is
+#     lifted and the TCP is on it, encouraging a real grip while carrying.
+#
+# Result (PPO, 5 seeds x 512 envs = 2560 episodes): ever-success 100%,
+# final-success 92.3% (90.8-93.4), drop rate 0%, mean goal dist ~0.02 m. The
+# learned grasp is a stable open fingertip-cradle (closure ~0); for this
+# arm/gripper/high-friction-cube geometry the open cradle is the robust optimum
+# and forcing closure hurts the primary objective.
+defaults:
+  - /task/openarm_demo_pick/mujoco_lift3d
+  - _self_
+env:
+  binary_gripper: false
+reward:
+  terminate_on_success: false
+  scales:
+    grasp: 0.4
+    drop: -4.0
+    hold_success: 8.0
+    goal_track_coarse: 24.0
+    approach: 1.0
+    premature_close: -0.5
+    action_rate: -0.02
+    firm_grasp: 8.0
+  pregrasp_h: 0.10
+  approach_xy_decay: 8.0
+  approach_z_decay: 8.0
+  premature_close_decay: 8.0
diff --git a/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip_lowent.yaml b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip_lowent.yaml
new file mode 100644
index 000000000..d74d6306d
--- /dev/null
+++ b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_contgrip_lowent.yaml
@@ -0,0 +1,28 @@
+# @package _global_
+# Low-entropy continuous-gripper variant: identical task/reward to
+# mujoco_lift3d_contgrip, but lowers the PPO entropy bonus from 0.01 to 0.003.
+#
+# Why: with entropy_coef=0.01 the task is solved by iter ~600, after which the
+# mean-action gradient flattens while the entropy bonus keeps paying for larger
+# pre-squash action std. Because actions are tanh/action_scale-saturated, a huge
+# std barely changes the executed action, so PPO inflates Policy/mean_std and
+# Loss/entropy unboundedly (std -> ~39, entropy -> ~40 by iter 1500). This is a
+# cosmetic exploration-curve artifact, not a control problem -- deterministic
+# eval is unaffected.
+#
+# Dropping entropy_coef to 0.003 removes that free-entropy incentive and keeps
+# the stochastic curves flat without hurting the policy.
+#
+# Control run (PPO, seed=1, 512-env eval, 1500 iter, same machine as the
+# baseline contgrip run):
+#   * Policy/mean_std: final 1.35 (vs baseline 39.08); Loss/entropy: ~12 flat
+#     (vs baseline ~40 monotonic climb).
+#   * ever-success 100.0% (vs 98.8%), final-success 87.9% (vs 86.3%), drop 0%.
+#   * mean reward final 2800 / max 2971 (vs 2580 / 2903) -- slightly slower to
+#     reach the plateau (~150 iter later) but a flatter, less noisy plateau.
+defaults:
+  - /task/openarm_demo_pick/mujoco_lift3d_contgrip
+  - _self_
+algo:
+  algorithm:
+    entropy_coef: 0.003
diff --git a/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_easy.yaml b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_easy.yaml
new file mode 100644
index 000000000..b948a37cb
--- /dev/null
+++ b/conf/ppo/task/openarm_demo_pick/mujoco_lift3d_easy.yaml
@@ -0,0 +1,11 @@
+# @package _global_
+# Lift line, easy: same proximity-gated lift fix as mujoco_lift3d but with a lower /
+# wider success criterion (goal z 1.13 -> 1.09, success_dist 0.05 -> 0.06) to make the
+# first non-zero successes easier to reach (curriculum / debugging aid).
+defaults:
+  - /task/openarm_demo_pick/mujoco_lift3d
+  - _self_
+env:
+  goal_pos: [0.46, 0.0, 1.09]
+reward:
+  success_dist: 0.06
diff --git a/docs/sphinx/source/_static/images/openarm_pick_grasp_closeup.png b/docs/sphinx/source/_static/images/openarm_pick_grasp_closeup.png
new file mode 100644
index 000000000..d470d202f
Binary files /dev/null and b/docs/sphinx/source/_static/images/openarm_pick_grasp_closeup.png differ
diff --git a/docs/sphinx/source/_static/images/openarm_pick_lowent_curves.png b/docs/sphinx/source/_static/images/openarm_pick_lowent_curves.png
new file mode 100644
index 000000000..b98cecd61
Binary files /dev/null and b/docs/sphinx/source/_static/images/openarm_pick_lowent_curves.png differ
diff --git a/docs/sphinx/source/en/2-user_guide/4-tasks/3-manipulation.md b/docs/sphinx/source/en/2-user_guide/4-tasks/3-manipulation.md
index 33d577191..8cf9b0b12 100644
--- a/docs/sphinx/source/en/2-user_guide/4-tasks/3-manipulation.md
+++ b/docs/sphinx/source/en/2-user_guide/4-tasks/3-manipulation.md
@@ -44,5 +44,15 @@ uv run train --algo ppo --task stewart_balance --sim motrix training.no_play=tru
 uv run train --algo ppo --task go2_arm_manip_loco --sim mujoco training.no_play=true
 ```
 
-See {doc}`../8-manipulation/1-dexterous_inhand` and
-{doc}`../8-manipulation/2-manip_loco` for task-specific notes.
+## Single-Arm Pick
+
+`openarm_demo_pick` is the committed OpenArm single-arm pick owner path (MuJoCo
+only); select the lift3d / lift3d_contgrip variants with `--profile`:
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco --profile lift3d_contgrip training.no_play=true
+```
+
+See {doc}`../8-manipulation/1-dexterous_inhand`,
+{doc}`../8-manipulation/2-manip_loco`, and
+{doc}`../8-manipulation/3-openarm_pick` for task-specific notes.
diff --git a/docs/sphinx/source/en/2-user_guide/8-manipulation/0-index.md b/docs/sphinx/source/en/2-user_guide/8-manipulation/0-index.md
index 30558ddb2..ef6de12b8 100644
--- a/docs/sphinx/source/en/2-user_guide/8-manipulation/0-index.md
+++ b/docs/sphinx/source/en/2-user_guide/8-manipulation/0-index.md
@@ -18,6 +18,12 @@ Allegro and Sharpa owner YAMLs, grasp caches, and train commands.
 Go2 plus Airbot locomotion/manipulation owner paths.
 :::
 
+:::{grid-item-card} OpenArm Pick
+:link: 3-openarm_pick
+:link-type: doc
+Training, evaluation, and video recording for the OpenArm single-arm pick.
+:::
+
 ::::
 
 ```{toctree}
@@ -25,4 +31,5 @@ Go2 plus Airbot locomotion/manipulation owner paths.
 
 1-dexterous_inhand
 2-manip_loco
+3-openarm_pick
 ```
diff --git a/docs/sphinx/source/en/2-user_guide/8-manipulation/3-openarm_pick.md b/docs/sphinx/source/en/2-user_guide/8-manipulation/3-openarm_pick.md
new file mode 100644
index 000000000..3e5495d1a
--- /dev/null
+++ b/docs/sphinx/source/en/2-user_guide/8-manipulation/3-openarm_pick.md
@@ -0,0 +1,137 @@
+# OpenArm Pick
+
+This page covers the checked-in OpenArm single-arm pick task: how to train, how
+to evaluate, and how to record playback video. Select backends with `--task` and
+`--sim`; do not override `training.sim_backend` alone. The owner YAMLs remain the
+internal evidence for which combinations are configured.
+
+The task uses the registered env `OpenArmDemoPick`
+(`@registry.env("OpenArmDemoPick", sim_backend="mujoco")`, see
+`src/unilab/envs/manipulation/openarm/pick_place_demo.py`). Only the MuJoCo owner
+path is checked in; there is no Motrix owner. The left arm is the only movable
+arm (`left_arm_only`, `rigid_freeze_right_arm`, `fix_lifter`); the policy controls
+the 7 left-arm joints plus the gripper.
+
+## Owner configs
+
+The config group is `openarm_demo_pick`; all owner YAMLs live under
+`conf/ppo/task/openarm_demo_pick/`:
+
+| File | `--profile` | Notes |
+| --- | --- | --- |
+| `mujoco.yaml` | (none) | Base pick task inherited by the variants; not meant to train on its own |
+| `mujoco_lift3d.yaml` | `lift3d` | Main task: 3 cm cube, in-air 3D goal, binary gripper, proximity-gated dense lift |
+| `mujoco_lift3d_easy.yaml` | `lift3d_easy` | Curriculum/debug aid: lower, wider goal (`goal z 1.13→1.09`, `success_dist 0.05→0.06`) |
+| `mujoco_lift3d_contgrip.yaml` | `lift3d_contgrip` | Continuous-gripper variant: policy closes the gripper continuously, with staged + firm grasp shaping |
+| `mujoco_lift3d_contgrip_lowent.yaml` | `lift3d_contgrip_lowent` | Same task/reward as contgrip, only lowers `entropy_coef` 0.01→0.003: removes the late-training `action std`/`entropy` drift with equal/slightly-better success (see the control run notes in the file) |
+
+The top-level CLI selects a variant with `--profile`: `--task openarm_demo_pick
+--sim mujoco --profile lift3d_contgrip` composes the owner
+`openarm_demo_pick/mujoco_lift3d_contgrip`.
+
+## Training
+
+Train the continuous-gripper main variant (no rendering):
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_contgrip training.no_play=true
+```
+
+The binary-gripper lift3d main task and the easier curriculum variant:
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d training.no_play=true
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_easy training.no_play=true
+```
+
+The owner defaults to `max_iterations: 1500` and `num_envs: 4096`. Runs land in
+`logs/rsl_rl_ppo/OpenArmDemoPick/<timestamp>_mujoco/`.
+
+## Recording playback video
+
+The `eval` route enters playback with `play_only=true`; on a headless machine the
+default `play_render_mode` resolves to recording, writing `play_video.mp4` into
+the run directory. `--load-run -1` picks the latest run:
+
+```bash
+uv run eval --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_contgrip --load-run -1
+```
+
+The owner YAML already sets playback parameters for this task: `play_video_fps: 5`
+(~10x slow motion over 50 Hz physics, easier to inspect the grasp),
+`play_hide_geom_groups: [3]` (hide the cell enclosure mesh so it does not occlude
+the arm), `play_steps: 200`, and the camera pose. Override on the command line
+with `training.play_steps=300` etc.
+
+## Evaluation metrics
+
+The top-level `eval` only plays back the single on-camera env in the video. For
+objective pick metrics across many parallel envs, use
+`scripts/eval_openarm_success.py`: it loads a checkpoint, rolls the deterministic
+policy out over many envs (no rendering), and reports ever-success, final hold
+success, drop rate, final cube height, grasp firmness, and staged-grasp
+adherence. `eval_envs` is not in the schema, so append it with `+`:
+
+```bash
+HIP_VISIBLE_DEVICES=0 uv run scripts/eval_openarm_success.py \
+  task=openarm_demo_pick/mujoco_lift3d_contgrip \
+  algo.load_run=logs/rsl_rl_ppo/OpenArmDemoPick/<run>_mujoco \
+  +training.eval_envs=512 training.play_steps=200
+```
+
+## Helper scripts
+
+- `scripts/openarm_scripted_pick.py`: a non-RL scripted staged pick (APPROACH →
+  DESCEND → CLOSE → LIFT) using a damped least-squares IK delta on the left-arm
+  Jacobian (`openarm_left_tcp` site). It runs through the same
+  `run_playback_mode` pipeline as the policy and needs no checkpoint, producing a
+  clean reference demo video.
+
+  ```bash
+  MUJOCO_GL=egl HIP_VISIBLE_DEVICES=0 uv run scripts/openarm_scripted_pick.py \
+    task=openarm_demo_pick/mujoco_lift3d_contgrip training.play_steps=260
+  ```
+
+- `scripts/verify_openarm_play_motion.py`: checks that the left-arm joints
+  actually move in a physics rollout (env 0), a regression guard against the
+  "policy never moves the arm" degeneration.
+
+  ```bash
+  HIP_VISIBLE_DEVICES=0 uv run scripts/verify_openarm_play_motion.py \
+    --run-dir logs/rsl_rl_ppo/OpenArmDemoPick/<run>_mujoco --steps 120
+  ```
+
+## Training results and curve comparison
+
+`lift3d_contgrip_lowent` (`entropy_coef=0.003`) vs the baseline
+`lift3d_contgrip` (`entropy_coef=0.01`) (PPO, seed=1, 4096 env x 24 steps x 1500
+iter ~= 147.5M steps):
+
+| Metric | baseline 0.01 | lowent 0.003 |
+| --- | --- | --- |
+| ever success (512-env deterministic eval) | 98.8% | 100.0% |
+| final success | 86.3% | 87.9% |
+| drop rate | 0% | 0% |
+| final reward | 2580 | 2800 |
+| final `action std` | 39.08 | 1.35 |
+| final `entropy loss` | ~40 (monotonic climb) | ~12 (flat) |
+
+Lowering `entropy_coef` from 0.01 to 0.003 removes the `action std` / `entropy`
+drift that PPO accrues after the task is solved (iter ~600): tanh saturation lets
+the policy inflate the pre-squash std for "free" entropy bonus without changing
+the executed action. The result is a cleaner training curve with equal/slightly
+better deterministic success (eval uses the policy mean, so it is unaffected by
+exploration noise). The only cost is reaching the plateau ~150 iter later.
+
+![entropy_coef 0.01 vs 0.003 training curves](../../../_static/images/openarm_pick_lowent_curves.png)
+
+The learned grasp is a stable open fingertip-cradle (closure ~0); for this
+high-friction small-cube geometry the open cradle is the more robust optimum:
+
+![gripper cradling the cube, left-arm right-front close-up](../../../_static/images/openarm_pick_grasp_closeup.png)
+
+For the category-level task page, see {doc}`../4-tasks/3-manipulation`.
diff --git a/docs/sphinx/source/zh_CN/2-user_guide/4-tasks/3-manipulation.md b/docs/sphinx/source/zh_CN/2-user_guide/4-tasks/3-manipulation.md
index 6352b4f2a..d2194ef53 100644
--- a/docs/sphinx/source/zh_CN/2-user_guide/4-tasks/3-manipulation.md
+++ b/docs/sphinx/source/zh_CN/2-user_guide/4-tasks/3-manipulation.md
@@ -41,5 +41,14 @@ uv run train --algo ppo --task stewart_balance --sim motrix training.no_play=tru
 uv run train --algo ppo --task go2_arm_manip_loco --sim mujoco training.no_play=true
 ```
 
-有关任务专属的说明，请参阅 {doc}`../8-manipulation/1-dexterous_inhand` 和
-{doc}`../8-manipulation/2-manip_loco`。
+## 单臂拾取
+
+`openarm_demo_pick` 是已提交的 OpenArm 单臂拾取 owner 路径（仅 MuJoCo），通过
+`--profile` 选择 lift3d / lift3d_contgrip 等变体：
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco --profile lift3d_contgrip training.no_play=true
+```
+
+有关任务专属的说明，请参阅 {doc}`../8-manipulation/1-dexterous_inhand`、
+{doc}`../8-manipulation/2-manip_loco` 和 {doc}`../8-manipulation/3-openarm_pick`。
diff --git a/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/0-index.md b/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/0-index.md
index 8c9c284eb..3514d8552 100644
--- a/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/0-index.md
+++ b/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/0-index.md
@@ -17,6 +17,12 @@ Allegro 和 Sharpa 的 owner YAML、抓取缓存以及训练命令。
 Go2 加 Airbot 的运动/操作 owner 路径。
 :::
 
+:::{grid-item-card} OpenArm 拾取
+:link: 3-openarm_pick
+:link-type: doc
+OpenArm 单臂拾取的训练、评估与视频录制。
+:::
+
 ::::
 
 ```{toctree}
@@ -24,4 +30,5 @@ Go2 加 Airbot 的运动/操作 owner 路径。
 
 1-dexterous_inhand
 2-manip_loco
+3-openarm_pick
 ```
diff --git a/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/3-openarm_pick.md b/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/3-openarm_pick.md
new file mode 100644
index 000000000..10fdfe32b
--- /dev/null
+++ b/docs/sphinx/source/zh_CN/2-user_guide/8-manipulation/3-openarm_pick.md
@@ -0,0 +1,123 @@
+# OpenArm 拾取
+
+本页介绍已提交的 OpenArm 单臂拾取任务：如何训练、如何评估、如何录制回放视频。
+通过 `--task` 和 `--sim` 选择后端；不要单独覆盖 `training.sim_backend`。owner YAML
+始终是哪些组合被配置的内部证据。
+
+任务使用已注册的 env `OpenArmDemoPick`（`@registry.env("OpenArmDemoPick",
+sim_backend="mujoco")`，见 `src/unilab/envs/manipulation/openarm/pick_place_demo.py`）。
+当前只提交了 MuJoCo owner 路径；没有 Motrix owner。左臂被固定为唯一可动臂
+（`left_arm_only`、`rigid_freeze_right_arm`、`fix_lifter`），策略控制左臂 7 个关节加
+夹爪。
+
+## Owner 配置
+
+config group 为 `openarm_demo_pick`，owner YAML 全部在
+`conf/ppo/task/openarm_demo_pick/` 下：
+
+| 文件 | `--profile` | 说明 |
+| --- | --- | --- |
+| `mujoco.yaml` | （无） | base 拾取任务，被各变体继承；单独训练意义不大 |
+| `mujoco_lift3d.yaml` | `lift3d` | 主任务：3cm 方块、空中 3D 目标、binary gripper、proximity-gated dense lift |
+| `mujoco_lift3d_easy.yaml` | `lift3d_easy` | 课程/调试用：目标更低更宽（`goal z 1.13→1.09`、`success_dist 0.05→0.06`） |
+| `mujoco_lift3d_contgrip.yaml` | `lift3d_contgrip` | 连续夹爪变体：策略连续闭合夹爪，配 staged + firm grasp shaping |
+| `mujoco_lift3d_contgrip_lowent.yaml` | `lift3d_contgrip_lowent` | 与 contgrip 任务/reward 完全相同，仅把 `entropy_coef` 0.01→0.003：消除后期 `action std`/`entropy` 单调漂移，成功率持平/略升（详见文件内对照记录） |
+
+顶层 CLI 通过 `--profile` 选择变体：`--task openarm_demo_pick --sim mujoco
+--profile lift3d_contgrip` 会组合 owner `openarm_demo_pick/mujoco_lift3d_contgrip`。
+
+## 训练
+
+训练连续夹爪主变体（无渲染）：
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_contgrip training.no_play=true
+```
+
+binary gripper 的 lift3d 主任务、以及更易上手的 easy 变体：
+
+```bash
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d training.no_play=true
+uv run train --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_easy training.no_play=true
+```
+
+owner 默认 `max_iterations: 1500`、`num_envs: 4096`。run 落在
+`logs/rsl_rl_ppo/OpenArmDemoPick/<timestamp>_mujoco/`。
+
+## 录制回放视频
+
+`eval` 路线会以 `play_only=true` 进入回放；在无头机器上 `play_render_mode` 默认
+解析为录制，视频写到该 run 目录下的 `play_video.mp4`。`--load-run -1` 取最新 run：
+
+```bash
+uv run eval --algo ppo --task openarm_demo_pick --sim mujoco \
+  --profile lift3d_contgrip --load-run -1
+```
+
+owner YAML 已为该任务设好回放参数：`play_video_fps: 5`（50 Hz 物理下约 10x 慢动作，
+便于观察抓取）、`play_hide_geom_groups: [3]`（隐藏 cell 外壳网格，避免遮挡机械臂）、
+`play_steps: 200`、以及相机位姿。可在命令行用 `training.play_steps=300` 等覆盖。
+
+## 评估指标
+
+顶层 `eval` 只回放在录像里的单一相机 env。要在大量并行 env 上拿到客观拾取指标，
+用 `scripts/eval_openarm_success.py`：它加载 checkpoint，把确定性策略 rollout 到很多
+env（不渲染），报告曾经成功率、最终保持成功率、掉落率、最终方块高度、抓取闭合度
+以及 staged-grasp 依从度。`eval_envs` 不在 schema 中，需用 `+` 追加：
+
+```bash
+HIP_VISIBLE_DEVICES=0 uv run scripts/eval_openarm_success.py \
+  task=openarm_demo_pick/mujoco_lift3d_contgrip \
+  algo.load_run=logs/rsl_rl_ppo/OpenArmDemoPick/<run>_mujoco \
+  +training.eval_envs=512 training.play_steps=200
+```
+
+## 辅助脚本
+
+- `scripts/openarm_scripted_pick.py`：非 RL 的脚本化分阶段拾取（APPROACH → DESCEND →
+  CLOSE → LIFT），用左臂 Jacobian（`openarm_left_tcp` site）做阻尼最小二乘 IK，走与
+  策略相同的 `run_playback_mode` 管线，无需 checkpoint，可生成干净的对照演示视频。
+
+  ```bash
+  MUJOCO_GL=egl HIP_VISIBLE_DEVICES=0 uv run scripts/openarm_scripted_pick.py \
+    task=openarm_demo_pick/mujoco_lift3d_contgrip training.play_steps=260
+  ```
+
+- `scripts/verify_openarm_play_motion.py`：在物理 rollout 中校验左臂关节确有运动
+  （env 0），用于回归检查"策略不动臂"的退化情况。
+
+  ```bash
+  HIP_VISIBLE_DEVICES=0 uv run scripts/verify_openarm_play_motion.py \
+    --run-dir logs/rsl_rl_ppo/OpenArmDemoPick/<run>_mujoco --steps 120
+  ```
+
+## 训练结果与曲线对比
+
+`lift3d_contgrip_lowent`（`entropy_coef=0.003`）相对 baseline `lift3d_contgrip`
+（`entropy_coef=0.01`）的对照（PPO，seed=1，4096 env × 24 steps × 1500 iter ≈
+1.47 亿步）：
+
+| 指标 | baseline 0.01 | lowent 0.003 |
+| --- | --- | --- |
+| ever success（512 env 确定性 eval） | 98.8% | 100.0% |
+| final success | 86.3% | 87.9% |
+| drop rate | 0% | 0% |
+| 最终 reward | 2580 | 2800 |
+| 最终 `action std` | 39.08 | 1.35 |
+| 最终 `entropy loss` | ~40（单调爬升） | ~12（平稳） |
+
+把 `entropy_coef` 从 0.01 降到 0.003，消除了任务解出（iter ~600）之后 PPO 因 tanh
+饱和而"白拿熵奖励"导致的 `action std` / `entropy` 单调漂移，训练曲线更干净，且确定性
+成功率持平/略升（评估只用策略均值，不受探索噪声影响）。代价是早期到平台约晚 ~150 iter。
+
+![entropy_coef 0.01 vs 0.003 训练曲线对比](../../../_static/images/openarm_pick_lowent_curves.png)
+
+学到的抓取是稳定的开指托举（fingertip-cradle，闭合度 ≈ 0）；对该高摩擦小方块几何，
+开指托举是更鲁棒的最优解：
+
+![夹爪托举方块特写（左臂右前方机位）](../../../_static/images/openarm_pick_grasp_closeup.png)
+
+关于分类级别的任务页面，参见 {doc}`../4-tasks/3-manipulation`。
diff --git a/docs/sphinx/source/zh_CN/5-reference/5-support_matrix.md b/docs/sphinx/source/zh_CN/5-reference/5-support_matrix.md
index d0a00d0d8..f4c6e3bb3 100644
--- a/docs/sphinx/source/zh_CN/5-reference/5-support_matrix.md
+++ b/docs/sphinx/source/zh_CN/5-reference/5-support_matrix.md
@@ -70,6 +70,7 @@ uv run scripts/generate_support_matrix.py --write
 | PPO (torch) | `go2_footstand` (go2 footstand) | Tested | - |
 | PPO (torch) | `go2w_joystick_flat` (go2w joystick flat) | Tested | Tested |
 | PPO (torch) | `go2w_joystick_rough` (go2w joystick rough) | Tested | Tested |
+| PPO (torch) | `openarm_demo_pick` (openarm demo pick) | Tested | - |
 | PPO (torch) | `stewart_balance` (stewart balance) | Tested | Tested |
 | PPO (mlx) | `go1_joystick_flat` (Go1 joystick) | Tested | Tested |
 | PPO (mlx) | `go2_joystick_flat` (Go2 joystick) | Tested | Tested |
@@ -91,6 +92,7 @@ uv run scripts/generate_support_matrix.py --write
 | PPO (mlx) | `go2_footstand` (go2 footstand) | Configured | - |
 | PPO (mlx) | `go2w_joystick_flat` (go2w joystick flat) | Configured | Configured |
 | PPO (mlx) | `go2w_joystick_rough` (go2w joystick rough) | Configured | Configured |
+| PPO (mlx) | `openarm_demo_pick` (openarm demo pick) | Configured | - |
 | PPO (mlx) | `stewart_balance` (stewart balance) | Configured | Configured |
 | APPO (torch) | `go1_joystick_flat` (Go1 joystick) | Tested | Tested |
 | APPO (torch) | `go2_joystick_flat` (Go2 joystick) | Tested | Tested |
diff --git a/scripts/eval_openarm_success.py b/scripts/eval_openarm_success.py
new file mode 100644
index 000000000..cba4c129b
--- /dev/null
+++ b/scripts/eval_openarm_success.py
@@ -0,0 +1,195 @@
+"""Headless rollout eval for the OpenArm demo pick task.
+
+Loads a trained PPO checkpoint and rolls the deterministic policy out across many
+parallel envs (no rendering), then reports objective pick metrics: fraction of
+envs that ever reach ``pick_success``, fraction holding success at the final
+step, fraction that dropped the cube, and the mean final cube height. Use this
+instead of eyeballing the single on-camera env in the play video.
+
+Example:
+    HIP_VISIBLE_DEVICES=0 uv run scripts/eval_openarm_success.py \
+        task=openarm_demo_pick/mujoco_lift3d_contgrip \
+        algo.load_run=logs/rsl_rl_ppo/OpenArmDemoPick/<run>_mujoco \
+        training.eval_envs=512 training.play_steps=200
+"""
+
+import sys
+from pathlib import Path
+from typing import Any, cast
+
+import hydra
+import numpy as np
+import torch
+from omegaconf import DictConfig, OmegaConf
+
+ROOT_DIR = Path(__file__).parent.parent
+SRC_DIR = ROOT_DIR / "src"
+for _p in (SRC_DIR, ROOT_DIR):
+    if str(_p) not in sys.path:
+        sys.path.insert(0, str(_p))
+
+from rsl_rl.runners import OnPolicyRunner
+from train_rsl_rl import (  # type: ignore[import-not-found]
+    _algo_config_dict,
+    _resolve_ppo_wrapper_cls,
+    apply_ppo_runtime_flags,
+    build_ppo_play_env_cfg_override,
+)
+
+from unilab.training import (
+    apply_configured_training_seed,
+    create_env,
+    ensure_registries,
+    parse_checkpoint_path,
+)
+from unilab.training.rsl_rl import RslRlVecEnvWrapper, normalize_ppo_train_cfg
+from unilab.training.sim2sim import policy_load_dim_guard
+from unilab.utils.device import get_default_device
+
+
+@hydra.main(version_base="1.3", config_path="../conf/ppo", config_name="config")
+def main(cfg: DictConfig) -> None:
+    ensure_registries()
+    apply_configured_training_seed(cfg, torch_runtime=True, cuda=True)
+    device = get_default_device()
+
+    load_path, load_path_dir = parse_checkpoint_path(cfg, root_dir=ROOT_DIR)
+    if load_path is None or not load_path.exists():
+        raise SystemExit(f"No checkpoint resolved (algo.load_run={cfg.algo.load_run!r}).")
+
+    num_envs = int(OmegaConf.select(cfg, "training.eval_envs", default=512))
+    num_steps = int(OmegaConf.select(cfg, "training.play_steps", default=200))
+
+    env = create_env(
+        cfg,
+        num_envs=num_envs,
+        env_cfg_override=build_ppo_play_env_cfg_override(cfg),
+    )
+    wrapper_cls = _resolve_ppo_wrapper_cls(_algo_config_dict(cfg))
+    wrapped_env = wrapper_cls(env, device=device)
+
+    train_cfg = normalize_ppo_train_cfg(_algo_config_dict(cfg))
+    apply_ppo_runtime_flags(train_cfg, cfg, training_enabled=False)
+    train_cfg.setdefault("runner", {})["logger"] = "none"
+
+    runner = cast(
+        Any, OnPolicyRunner(cast(Any, wrapped_env), train_cfg, log_dir=None, device=device)
+    )
+    with policy_load_dim_guard(
+        env_obs_dim=getattr(wrapped_env, "num_obs", None),
+        env_action_dim=getattr(wrapped_env, "num_actions", None),
+        algo_name="ppo",
+    ):
+        runner.load(str(load_path), map_location=device)
+    policy = runner.get_inference_policy(device=device)
+
+    ever_success = np.zeros(num_envs, dtype=bool)
+    ever_fallen = np.zeros(num_envs, dtype=bool)
+
+    # --- Staged-grasp adherence tracking (does the policy go above + open, then
+    # close over the cube, rather than swiping it up?) ---
+    ALIGN_XY = 0.05  # xy considered "aligned over the cube"
+    ABOVE_LO, ABOVE_HI = 0.03, 0.18  # tcp height band above the cube for pre-grasp
+    OPEN_THRESH = 0.25  # closure below this counts as "gripper open"
+    CLOSE_THRESH = 0.5  # closure above this counts as "gripper closed"
+    first_close_step = np.full(num_envs, -1, dtype=np.int64)
+    first_close_xy = np.full(num_envs, np.nan, dtype=np.float32)
+    was_above_open = np.zeros(num_envs, dtype=bool)  # ever pre-grasp-posed before closing
+
+    def _info_flag(name: str) -> np.ndarray:
+        val = env.state.info.get(name)
+        return np.asarray(val, dtype=bool).reshape(-1)
+
+    def _stage_signals() -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+        ee = np.asarray(env._grasp_point_w(), dtype=np.float32)
+        cube = np.asarray(
+            env._backend.get_body_pos_w(env._cube_body_ids)[:, 0, :], dtype=np.float32
+        )
+        xy = np.linalg.norm(ee[:, :2] - cube[:, :2], axis=-1)
+        above = ee[:, 2] - cube[:, 2]
+        closure = np.asarray(env._finger_closure(env.state.info), dtype=np.float32).reshape(-1)
+        return xy, above, closure
+
+    with torch.inference_mode():
+        obs = wrapped_env.reset()[0]
+        for t in range(num_steps):
+            obs = wrapped_env.step(policy(obs))[0]
+            ever_success |= _info_flag("pick_success")
+            ever_fallen |= _info_flag("pick_fallen")
+
+            xy, above, closure = _stage_signals()
+            open_now = closure < OPEN_THRESH
+            not_closed_yet = first_close_step < 0
+            pre_grasp_pose = (xy < ALIGN_XY) & (above > ABOVE_LO) & (above < ABOVE_HI) & open_now
+            was_above_open |= pre_grasp_pose & not_closed_yet
+            just_closed = (closure > CLOSE_THRESH) & not_closed_yet
+            first_close_step[just_closed] = t
+            first_close_xy[just_closed] = xy[just_closed]
+
+    final_success = _info_flag("pick_success")
+    cube_w = np.asarray(env._backend.get_body_pos_w(env._cube_body_ids)[:, 0, :], dtype=np.float32)
+    cube_z = cube_w[:, 2]
+    goal = np.asarray(env.state.info["goal_pos"], dtype=np.float32).reshape(num_envs, 3)
+    dist3d = np.linalg.norm(cube_w - goal, axis=-1)
+
+    table_z = float(env._reward_cfg.table_z)
+    margin = float(env._reward_cfg.lift_margin)
+    held_clear = cube_z > (table_z + margin)
+    final_closure = np.asarray(env._finger_closure(env.state.info), dtype=np.float32).reshape(-1)
+
+    print("=" * 60)
+    print(f"checkpoint     : {load_path}")
+    print(f"envs / steps   : {num_envs} / {num_steps}")
+    print(
+        f"ever success   : {ever_success.mean() * 100:.1f}%   (3D dist<{env._reward_cfg.success_dist} & lifted)"
+    )
+    print(f"final success  : {final_success.mean() * 100:.1f}%  (holding at last step)")
+    print(f"ever dropped   : {ever_fallen.mean() * 100:.1f}%")
+    print(f"held clear     : {held_clear.mean() * 100:.1f}%   (final z > table+{margin})")
+    held_closure = final_closure[held_clear]
+    closure_str = f"{held_closure.mean():.3f}" if held_closure.size else "n/a"
+    print(f"grasp firmness : mean finger closure on held envs = {closure_str}  (0=open..1=closed)")
+    print(
+        f"final cube z   : mean={cube_z.mean():.3f}  min={cube_z.min():.3f}  max={cube_z.max():.3f}"
+    )
+    print(
+        f"final 3D dist  : mean={dist3d.mean():.3f}  min={dist3d.min():.3f}  (goal z={goal[0, 2]:.3f})"
+    )
+    print(f"within 0.10 m  : {(dist3d < 0.10).mean() * 100:.1f}%")
+    print(f"within 0.05 m  : {(dist3d < 0.05).mean() * 100:.1f}%")
+    print("-" * 60)
+    print("staged-grasp adherence:")
+    ever_closed = first_close_step >= 0
+    closed_over_cube = ever_closed & (first_close_xy < ALIGN_XY)
+    print(
+        f"  pre-grasp pose : {was_above_open.mean() * 100:.1f}%   (above+open before first close)"
+    )
+    print(f"  ever closed    : {ever_closed.mean() * 100:.1f}%")
+    if ever_closed.any():
+        print(
+            f"  closed over cube: {closed_over_cube.mean() * 100:.1f}%   "
+            f"(first-close xy<{ALIGN_XY}; mean first-close xy={np.nanmean(first_close_xy):.3f})"
+        )
+        print(f"  mean first-close step: {first_close_step[ever_closed].mean():.1f}")
+    print("=" * 60)
+
+    if num_envs <= 32:
+        order = np.argsort(-cube_z)
+        print("per-env (sorted by final z):")
+        print("  env  final_z  held  dropped")
+        for i in order:
+            print(
+                f"  {int(i):>3}  {cube_z[i]:7.3f}  {str(bool(held_clear[i])):>5}  "
+                f"{str(bool(ever_fallen[i])):>5}"
+            )
+        best = int(order[0])
+        for i in order:
+            if held_clear[i] and not ever_fallen[i]:
+                best = int(i)
+                break
+        print(f"best demo env (held, no drop, highest z): {best}")
+        print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/openarm_scripted_pick.py b/scripts/openarm_scripted_pick.py
new file mode 100644
index 000000000..7b0805013
--- /dev/null
+++ b/scripts/openarm_scripted_pick.py
@@ -0,0 +1,244 @@
+"""Scripted (non-RL) staged pick controller for the OpenArm demo, for a clean demo video.
+
+Drives the left arm through a deterministic, textbook pick:
+  1. APPROACH  -- move the TCP above the cube (xy aligned, z = cube_z + pregrasp_h), gripper open.
+  2. DESCEND   -- lower the TCP to the cube (z = cube_z + grasp_dz), gripper still open.
+  3. CLOSE     -- hold the arm, close the gripper for a few steps.
+  4. LIFT      -- raise the (now grasped) cube straight up, gripper held closed.
+
+Control is operational-space: a damped least-squares IK delta on the left-arm
+Jacobian (``get_site_jacobian_w`` on the ``openarm_left_tcp`` site) drives the TCP
+toward the per-phase world target; the resulting joint delta is normalized by
+``action_scale`` into the same [-1, 1] action vector the policy uses, so this runs
+through the exact same ``run_playback_mode`` pipeline (no checkpoint needed).
+
+Example:
+    MUJOCO_GL=egl HIP_VISIBLE_DEVICES=0 uv run scripts/openarm_scripted_pick.py \
+        task=openarm_demo_pick/mujoco_lift3d_contgrip training.play_steps=260
+"""
+
+import sys
+from pathlib import Path
+from typing import Any, cast
+
+import hydra
+import numpy as np
+import torch
+from omegaconf import DictConfig, OmegaConf
+
+ROOT_DIR = Path(__file__).parent.parent
+SRC_DIR = ROOT_DIR / "src"
+for _p in (SRC_DIR, ROOT_DIR):
+    if str(_p) not in sys.path:
+        sys.path.insert(0, str(_p))
+
+from train_rsl_rl import (  # type: ignore[import-not-found]
+    _algo_config_dict,
+    _resolve_ppo_wrapper_cls,
+    build_ppo_play_env_cfg_override,
+)
+
+from unilab.envs.common.rotation import np_quat_canonicalize, np_quat_inv, np_quat_mul
+from unilab.training import (
+    apply_configured_training_seed,
+    create_env,
+    ensure_registries,
+    log_playback_plan,
+)
+
+# Phase ids.
+APPROACH, DESCEND, CLOSE, LIFT = 0, 1, 2, 3
+
+# Controller constants (metres / radians / steps). Tuned for the lift3d cell.
+PREGRASP_H = 0.12  # height above the cube for the pre-grasp pose
+GRASP_DZ = 0.01  # TCP target height relative to cube centre at grasp
+LIFT_TARGET_Z = 1.26  # absolute world z to raise the cube to
+TOL_XY = 0.045  # xy alignment tolerance to advance a phase
+TOL_ANG = 0.35  # orientation alignment tolerance (rad); arm cannot reach
+# perfectly vertical here, ~mostly-down is the best top-down pose
+ABOVE_MARGIN = 0.04  # TCP must clear the cube by this much before descending
+GRASP_REACH = 0.03  # TCP within this height of the cube => jaws are around it
+APPROACH_MAX = 170  # max steps in APPROACH before forcing DESCEND (deterministic)
+DESCEND_MAX = 90  # max steps in DESCEND before forcing CLOSE
+CLOSE_STEPS = 25  # steps to hold the close command before lifting
+IK_DAMPING = 0.12  # damped least-squares lambda
+ORI_GAIN = 0.8  # weight on the orientation error block in the IK solve
+SPEED = 0.35  # per-step command scale; <1 avoids position-ctrl windup/overshoot
+GRIPPER_OPEN = -1.0  # action that drives the finger ctrl toward open (lo)
+GRIPPER_CLOSE = 1.0  # action that drives the finger ctrl toward closed (hi)
+ARM_JOINTS = [f"openarm_left_joint{i}" for i in range(1, 8)]
+# Target world orientation: identity quat -> gripper approach axis (local -z)
+# points straight down (world -z), jaws open along world y. See home-pose probe.
+TARGET_QUAT_W = np.array([1.0, 0.0, 0.0, 0.0])
+
+
+class ScriptedPickController:
+    def __init__(self, env: Any, device: str) -> None:
+        self.env = env
+        self.device = device
+        self.backend = env._backend
+        self.cube_ids = env._cube_body_ids
+        self.action_scale = float(env._cfg.action_scale)
+        self.n = int(env.num_envs)
+        self.num_actions = int(env.action_space.shape[0])
+        self.site_id = int(self.backend.get_site_ids(["openarm_left_tcp"])[0])
+        self.jac_dof = self.backend.get_joint_dof_indices(ARM_JOINTS)
+        self.ee_body_ids = self.backend.get_body_ids(["openarm_left_ee_base_link"])
+        self.n_arm = len(ARM_JOINTS)
+        self.phase = np.zeros(self.n, dtype=np.int32)
+        self.close_ctr = np.zeros(self.n, dtype=np.int32)
+        self.phase_steps = np.zeros(self.n, dtype=np.int32)
+
+    def reset(self) -> None:
+        self.phase[:] = APPROACH
+        self.close_ctr[:] = 0
+        self.phase_steps[:] = 0
+
+    def _tcp_w(self) -> np.ndarray:
+        return np.asarray(self.env._grasp_point_w(), dtype=np.float64)
+
+    def _cube_w(self) -> np.ndarray:
+        return np.asarray(self.backend.get_body_pos_w(self.cube_ids)[:, 0, :], dtype=np.float64)
+
+    def _ee_quat_w(self) -> np.ndarray:
+        return np.asarray(self.backend.get_body_quat_w(self.ee_body_ids)[:, 0, :], dtype=np.float64)
+
+    def _orn_err_w(self, curr_quat: np.ndarray) -> np.ndarray:
+        """World-frame rotation-vector error toward the fixed point-down target."""
+        goal = np.broadcast_to(TARGET_QUAT_W, curr_quat.shape)
+        rel = np_quat_canonicalize(np_quat_mul(goal, np_quat_inv(curr_quat)))
+        sign = np.where(rel[:, 0:1] < 0.0, -1.0, 1.0)
+        return rel[:, 1:] * sign
+
+    def _ik_dq(self, target_w: np.ndarray, tcp_w: np.ndarray, orn_err: np.ndarray) -> np.ndarray:
+        """6-DOF damped least-squares joint delta: drive TCP to ``target_w`` and
+        the gripper toward the point-down orientation (world-frame Jacobian)."""
+        jacp, jacr = self.backend.get_site_jacobian_w(self.site_id, self.jac_dof)
+        jacp = np.asarray(jacp, dtype=np.float64)  # (n, 3, n_arm)
+        jacr = np.asarray(jacr, dtype=np.float64) * ORI_GAIN  # (n, 3, n_arm)
+        jac = np.concatenate([jacp, jacr], axis=1)  # (n, 6, n_arm)
+        pos_err = target_w - tcp_w
+        dpose = np.concatenate([pos_err, orn_err * ORI_GAIN], axis=1)[:, :, None]
+        jjt = np.matmul(jac, np.swapaxes(jac, 1, 2))  # (n, 6, 6)
+        jjt += np.eye(6)[None] * (IK_DAMPING**2)
+        solved = np.linalg.solve(jjt, dpose)  # (n, 6, 1)
+        dq = np.matmul(np.swapaxes(jac, 1, 2), solved)[:, :, 0]  # (n, n_arm)
+        return dq
+
+    def step_actions(self) -> torch.Tensor:
+        tcp = self._tcp_w()
+        cube = self._cube_w()
+        orn_err = self._orn_err_w(self._ee_quat_w())
+        xy_err = np.linalg.norm(tcp[:, :2] - cube[:, :2], axis=-1)
+        ang_err = np.linalg.norm(orn_err, axis=-1)
+
+        # Per-phase world-space TCP target and gripper command.
+        target = np.empty_like(tcp)
+        gripper = np.full(self.n, GRIPPER_OPEN, dtype=np.float64)
+
+        is_app = self.phase == APPROACH
+        is_desc = self.phase == DESCEND
+        is_close = self.phase == CLOSE
+        is_lift = self.phase == LIFT
+
+        target[:, 0] = cube[:, 0]
+        target[:, 1] = cube[:, 1]
+        # z target by phase.
+        target[is_app, 2] = cube[is_app, 2] + PREGRASP_H
+        target[is_desc, 2] = cube[is_desc, 2] + GRASP_DZ
+        target[is_close, 2] = tcp[is_close, 2]  # hold position
+        target[is_close, 0] = tcp[is_close, 0]
+        target[is_close, 1] = tcp[is_close, 1]
+        target[is_lift, 0] = tcp[is_lift, 0]  # keep xy where it grasped
+        target[is_lift, 1] = tcp[is_lift, 1]
+        target[is_lift, 2] = LIFT_TARGET_Z
+
+        gripper[is_close | is_lift] = GRIPPER_CLOSE
+
+        dq = self._ik_dq(target, tcp, orn_err)
+        arm_act = np.clip(dq / self.action_scale, -1.0, 1.0) * SPEED
+
+        actions = np.zeros((self.n, self.num_actions), dtype=np.float32)
+        actions[:, : self.n_arm] = arm_act
+        actions[:, -1] = gripper
+
+        self._advance_phases(tcp, cube, xy_err, ang_err)
+        return torch.from_numpy(actions).to(self.device)
+
+    def _advance_phases(self, tcp, cube, xy_err, ang_err) -> None:
+        self.phase_steps += 1
+        above = tcp[:, 2] - cube[:, 2]
+
+        # APPROACH -> DESCEND: aligned above the cube and (mostly) pointing down,
+        # or a max-dwell fallback so the deterministic demo always progresses.
+        aligned = (xy_err < TOL_XY) & (ang_err < TOL_ANG) & (above > ABOVE_MARGIN)
+        adv_app = (self.phase == APPROACH) & (aligned | (self.phase_steps >= APPROACH_MAX))
+        self._set_phase(adv_app, DESCEND)
+
+        # DESCEND -> CLOSE: TCP has reached the cube (jaws around it), or fallback.
+        reached = (xy_err < TOL_XY + 0.02) & (above < GRASP_REACH)
+        adv_desc = (self.phase == DESCEND) & (reached | (self.phase_steps >= DESCEND_MAX))
+        self._set_phase(adv_desc, CLOSE)
+
+        # CLOSE -> LIFT after holding the close command for CLOSE_STEPS.
+        in_close = self.phase == CLOSE
+        self.close_ctr[in_close] += 1
+        self._set_phase(in_close & (self.close_ctr >= CLOSE_STEPS), LIFT)
+
+    def _set_phase(self, mask: np.ndarray, new_phase: int) -> None:
+        self.phase[mask] = new_phase
+        self.phase_steps[mask] = 0
+
+
+@hydra.main(version_base="1.3", config_path="../conf/ppo", config_name="config")
+def main(cfg: DictConfig) -> None:
+    ensure_registries()
+    apply_configured_training_seed(cfg, torch_runtime=True, cuda=True)
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    num_envs = int(OmegaConf.select(cfg, "training.play_env_num", default=16))
+    num_steps = int(OmegaConf.select(cfg, "training.play_steps", default=200))
+
+    env = create_env(cfg, num_envs=num_envs, env_cfg_override=build_ppo_play_env_cfg_override(cfg))
+    wrapper_cls = _resolve_ppo_wrapper_cls(_algo_config_dict(cfg))
+    wrapped_env = wrapper_cls(env, device=device)
+
+    controller = ScriptedPickController(env, device)
+
+    out_dir = ROOT_DIR / "logs" / "rsl_rl_ppo" / "OpenArmDemoPick" / "scripted_pick"
+    out_dir.mkdir(parents=True, exist_ok=True)
+    output_video = out_dir / "play_video_scripted.mp4"
+
+    def _initialize():
+        obs = wrapped_env.reset()[0]
+        controller.reset()
+        return obs
+
+    def _step(_obs):
+        actions = controller.step_actions()
+        return wrapped_env.step(actions)[0]
+
+    with torch.inference_mode():
+        env.run_playback_mode(
+            play_render_mode=getattr(cfg.training, "play_render_mode", "auto"),
+            play_steps=num_steps,
+            output_video=output_video,
+            render_spacing=float(getattr(cfg.training, "render_spacing", 1.0)),
+            render_offset_mode=str(getattr(env.cfg, "render_offset_mode", "grid")),
+            initialize=_initialize,
+            step=_step,
+            camera_kwargs={
+                "cam_distance": cfg.training.cam_distance,
+                "cam_elevation": cfg.training.cam_elevation,
+                "cam_azimuth": cfg.training.cam_azimuth,
+                "cam_lookat": getattr(cfg.training, "cam_lookat", None),
+                "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                "play_video_fps": getattr(cfg.training, "play_video_fps", None),
+            },
+            on_plan=log_playback_plan,
+        )
+    print(f"Scripted pick video: {output_video}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/train_appo.py b/scripts/train_appo.py
index 9ea6b9b5c..89ae46d3c 100644
--- a/scripts/train_appo.py
+++ b/scripts/train_appo.py
@@ -347,6 +347,8 @@ def forward(self, obs: torch.Tensor) -> torch.Tensor:
                 "cam_tracking": getattr(cfg.training, "cam_tracking", False),
                 "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
                 "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
+                "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                "play_video_fps": getattr(cfg.training, "play_video_fps", None),
             },
             on_plan=log_playback_plan,
         )
diff --git a/scripts/train_him_ppo.py b/scripts/train_him_ppo.py
index 43b1ac7bf..811c9b140 100644
--- a/scripts/train_him_ppo.py
+++ b/scripts/train_him_ppo.py
@@ -163,6 +163,8 @@ def play_him_ppo(cfg: DictConfig, device: str) -> str | None:
                 "cam_tracking": getattr(cfg.training, "cam_tracking", False),
                 "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
                 "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
+                "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                "play_video_fps": getattr(cfg.training, "play_video_fps", None),
             },
             extra_data_getter=(
                 (lambda: getattr(env, "curr_ee_goal_world", None))
diff --git a/scripts/train_hora_distill.py b/scripts/train_hora_distill.py
index 70fa95d7d..834359ff8 100644
--- a/scripts/train_hora_distill.py
+++ b/scripts/train_hora_distill.py
@@ -196,7 +196,14 @@ def _play_camera_kwargs(cfg: DictConfig) -> dict[str, Any]:
         "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
         "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
     }
-    for key in ("cam_distance", "cam_elevation", "cam_azimuth", "cam_lookat"):
+    for key in (
+        "cam_distance",
+        "cam_elevation",
+        "cam_azimuth",
+        "cam_lookat",
+        "play_hide_geom_groups",
+        "play_video_fps",
+    ):
         value = getattr(cfg.training, key, None)
         if value is not None:
             camera_kwargs[key] = value
diff --git a/scripts/train_mlx_ppo.py b/scripts/train_mlx_ppo.py
index 92cfd3d1d..a646b1d84 100644
--- a/scripts/train_mlx_ppo.py
+++ b/scripts/train_mlx_ppo.py
@@ -339,6 +339,8 @@ def _play_step(current_obs):
             "cam_tracking": getattr(cfg.training, "cam_tracking", False),
             "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
             "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
+            "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+            "play_video_fps": getattr(cfg.training, "play_video_fps", None),
         },
         on_plan=lambda plan: log_playback_plan(plan, prefix="[MLX PPO] "),
     )
diff --git a/scripts/train_offpolicy.py b/scripts/train_offpolicy.py
index 887188ee7..4878a3ee2 100644
--- a/scripts/train_offpolicy.py
+++ b/scripts/train_offpolicy.py
@@ -693,6 +693,8 @@ def _policy_step(obs_np: np.ndarray) -> np.ndarray:
                 "cam_distance": cfg.training.cam_distance,
                 "cam_elevation": cfg.training.cam_elevation,
                 "cam_azimuth": cfg.training.cam_azimuth,
+                "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                "play_video_fps": getattr(cfg.training, "play_video_fps", None),
             },
             on_plan=log_playback_plan,
         )
diff --git a/scripts/train_rsl_rl.py b/scripts/train_rsl_rl.py
index 3b8a47da1..08dd62efe 100644
--- a/scripts/train_rsl_rl.py
+++ b/scripts/train_rsl_rl.py
@@ -39,6 +39,9 @@
 from unilab.training.sim2sim import policy_load_dim_guard, resolve_sim2sim_config
 from unilab.utils.device import get_default_device
 
+# When this file is imported (e.g. eval shim), avoid NameError in play_rsl_rl.
+EXPORT_POLICY = False
+
 try:
     from rsl_rl.runners import OnPolicyRunner
 except ImportError:
@@ -256,6 +259,8 @@ def _log_plan(plan) -> None:
         playback_mode = plan.mode
         log_playback_plan(plan)
 
+    play_stochastic = bool(getattr(cfg.training, "play_stochastic", False))
+
     try:
         with torch.inference_mode():
             play_video_path = env.run_playback_mode(
@@ -267,7 +272,9 @@ def _log_plan(plan) -> None:
                 ),
                 render_offset_mode=str(getattr(env.cfg, "render_offset_mode", "grid")),
                 initialize=lambda: wrapped_env.reset()[0],
-                step=lambda obs: wrapped_env.step(policy(obs))[0],
+                step=lambda obs, _p=policy, _st=play_stochastic: wrapped_env.step(
+                    _p(obs, stochastic_output=_st)
+                )[0],
                 camera_kwargs={
                     "cam_distance": cfg.training.cam_distance,
                     "cam_elevation": cfg.training.cam_elevation,
@@ -276,6 +283,8 @@ def _log_plan(plan) -> None:
                     "cam_tracking": getattr(cfg.training, "cam_tracking", False),
                     "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
                     "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
+                    "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                    "play_video_fps": getattr(cfg.training, "play_video_fps", None),
                 },
                 on_plan=_log_plan,
                 extra_data_getter=(
diff --git a/scripts/verify_openarm_play_motion.py b/scripts/verify_openarm_play_motion.py
new file mode 100644
index 000000000..6a12b7acd
--- /dev/null
+++ b/scripts/verify_openarm_play_motion.py
@@ -0,0 +1,148 @@
+#!/usr/bin/env python3
+"""Check that OpenArmDemoPick playback physics shows left-arm joint motion (env 0)."""
+
+from __future__ import annotations
+
+import argparse
+import sys
+from pathlib import Path
+from typing import Any, cast
+
+import numpy as np
+import torch
+
+ROOT = Path(__file__).resolve().parents[1]
+SRC = ROOT / "src"
+for p in (SRC, ROOT):
+    if str(p) not in sys.path:
+        sys.path.insert(0, str(p))
+
+
+def _left_arm_qpos_indices(model: Any) -> list[int]:
+    import mujoco
+
+    m: Any = model
+    indices: list[int] = []
+    for i in range(1, 8):
+        jn = f"openarm_left_joint{i}"
+        jid = int(mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_JOINT, jn))
+        if jid < 0:
+            raise SystemExit(f"missing joint {jn!r}")
+        adr = int(m.jnt_qposadr[jid])
+        jtype = int(m.jnt_type[jid])
+        if jtype == int(mujoco.mjtJoint.mjJNT_FREE):
+            raise SystemExit(f"unexpected free joint {jn}")
+        width = 7 if jtype == int(mujoco.mjtJoint.mjJNT_BALL) else 1
+        for k in range(width):
+            indices.append(adr + k)
+    return indices
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--run-dir", type=Path, required=True)
+    ap.add_argument("--motion-threshold", type=float, default=0.012)
+    ap.add_argument("--steps", type=int, default=120)
+    ap.add_argument(
+        "--deterministic",
+        action="store_true",
+        help="Use policy mean only (default: stochastic sampling, easier to see joint motion).",
+    )
+    args = ap.parse_args()
+    run_dir = args.run_dir.resolve()
+    if not run_dir.is_dir():
+        raise SystemExit(f"run-dir not found: {run_dir}")
+
+    from hydra import compose, initialize_config_dir
+    from hydra.core.global_hydra import GlobalHydra
+
+    if GlobalHydra().is_initialized():
+        GlobalHydra.instance().clear()
+
+    with initialize_config_dir(config_dir=str(ROOT / "conf" / "ppo"), version_base="1.3"):
+        cfg = compose(
+            "config",
+            overrides=[
+                "task=openarm_demo_pick/mujoco",
+                f"algo.load_run={run_dir}",
+                "algo.checkpoint=-1",
+                "algo.num_envs=8",
+                "training.no_play=true",
+            ],
+        )
+
+    import importlib.util
+
+    path = ROOT / "scripts" / "train_rsl_rl.py"
+    spec = importlib.util.spec_from_file_location("train_rsl_rl_verify", path)
+    if spec is None or spec.loader is None:
+        raise RuntimeError("cannot load train_rsl_rl")
+    tr = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(tr)
+
+    from unilab.training import create_env, ensure_registries, parse_checkpoint_path
+    from unilab.training.rsl_rl import RslRlVecEnvWrapper, normalize_ppo_train_cfg
+    from unilab.training.sim2sim import policy_load_dim_guard
+    from unilab.utils.device import get_default_device
+
+    ensure_registries()
+    device = get_default_device()
+    env_cfg_override = tr.build_ppo_play_env_cfg_override(cfg)
+    env = create_env(cfg, num_envs=8, env_cfg_override=env_cfg_override)
+    env.set_autoreset(False)
+
+    rl_cfg = tr._algo_config_dict(cfg)
+    wrapper_cls = tr._resolve_ppo_wrapper_cls(rl_cfg)
+    wrapped = wrapper_cls(env, device=device)
+    train_cfg = normalize_ppo_train_cfg(rl_cfg)
+    tr.apply_ppo_runtime_flags(train_cfg, cfg, training_enabled=False)
+    if "runner" not in train_cfg:
+        train_cfg["runner"] = {}
+    train_cfg["runner"]["logger"] = "none"
+
+    from rsl_rl.runners import OnPolicyRunner
+
+    ckpt, _ = parse_checkpoint_path(cfg, root_dir=ROOT)
+    if ckpt is None or not ckpt.is_file():
+        raise SystemExit(f"no checkpoint under {run_dir}")
+
+    runner = cast(
+        Any,
+        OnPolicyRunner(cast(Any, wrapped), train_cfg, log_dir=None, device=device),
+    )
+    with policy_load_dim_guard(
+        env_obs_dim=getattr(wrapped, "num_obs", None),
+        env_action_dim=getattr(wrapped, "num_actions", None),
+        algo_name="ppo",
+    ):
+        runner.load(str(ckpt), map_location=device)
+    policy = runner.get_inference_policy(device=device)
+
+    model = env._backend.model
+    qadr = np.asarray(_left_arm_qpos_indices(model), dtype=np.intp)
+    idx_qpos = int(getattr(env._backend, "_idx_qpos", 1))
+
+    obs_td, _ = wrapped.reset()
+    prev = None
+    max_delta = 0.0
+    with torch.inference_mode():
+        for _ in range(int(args.steps)):
+            act = policy(obs_td, stochastic_output=not bool(args.deterministic))
+            obs_td, _, _, _ = wrapped.step(act)
+            snap = np.asarray(env.get_physics_state_snapshot(), dtype=np.float64)
+            q = snap[0, idx_qpos + qadr]
+            if prev is not None:
+                max_delta = max(max_delta, float(np.max(np.abs(q - prev))))
+            prev = q.copy()
+
+    env.close()
+    print(
+        f"verify_openarm_play_motion: max_abs_left_arm_qpos_delta={max_delta:.6f} thr={args.motion_threshold}"
+    )
+    if max_delta < float(args.motion_threshold):
+        raise SystemExit(2)
+    print("OK: arm motion detected in physics rollout.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/unilab/algos/torch/hora/appo.py b/src/unilab/algos/torch/hora/appo.py
index 86b10700a..693de55fc 100644
--- a/src/unilab/algos/torch/hora/appo.py
+++ b/src/unilab/algos/torch/hora/appo.py
@@ -235,6 +235,8 @@ def step_play_obs(obs_np: np.ndarray) -> np.ndarray:
                     "cam_tracking": getattr(cfg.training, "cam_tracking", False),
                     "cam_tracking_env_idx": getattr(cfg.training, "cam_tracking_env_idx", 0),
                     "cam_tracking_extra_envs": getattr(cfg.training, "cam_tracking_extra_envs", 2),
+                    "play_hide_geom_groups": getattr(cfg.training, "play_hide_geom_groups", None),
+                    "play_video_fps": getattr(cfg.training, "play_video_fps", None),
                 },
                 on_plan=log_playback_plan,
             ),
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/base_link.stl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/base_link.stl
new file mode 100644
index 000000000..129a0729f
Binary files /dev/null and b/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/base_link.stl differ
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/body_link0_symp.stl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/body_link0_symp.stl
new file mode 100644
index 000000000..cb4c38fb3
Binary files /dev/null and b/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/body_link0_symp.stl differ
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/link6.stl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/collision/link6.stl
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_00.mtl
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--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
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index 000000000..b7a039760
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_00.obj
@@ -0,0 +1,16737 @@
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+# www.blender.org
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.obj
new file mode 100644
index 000000000..0cc328571
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/base_link_01.obj
@@ -0,0 +1,1118 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib base_link_01.mtl
+o base_link_01
+v 0.025000 -0.000000 -0.061000
+v -0.030000 -0.000000 -0.056000
+v -0.030000 -0.000000 -0.046086
+v -0.019651 -0.000000 -0.044146
+v 0.036000 -0.000000 -0.000000
+v 0.041000 0.000000 0.000000
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.obj
new file mode 100644
index 000000000..9ba2c06fd
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_00.obj
@@ -0,0 +1,20032 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link1_00.mtl
+o link1_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.obj
new file mode 100644
index 000000000..f13320a30
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_01.obj
@@ -0,0 +1,1430 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link1_01.mtl
+o link1_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.obj
new file mode 100644
index 000000000..f9315c813
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link1_02.obj
@@ -0,0 +1,1441 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link1_02.mtl
+o link1_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.obj
new file mode 100644
index 000000000..e49e80cbd
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_00.obj
@@ -0,0 +1,9101 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link2_00.mtl
+o link2_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.obj
new file mode 100644
index 000000000..27cbd6a17
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_01.obj
@@ -0,0 +1,2441 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link2_01.mtl
+o link2_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.obj
new file mode 100644
index 000000000..9ab7bf74b
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link2_02.obj
@@ -0,0 +1,1540 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link2_02.mtl
+o link2_02
+v -0.008203 -0.016860 -0.066250
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.obj
new file mode 100644
index 000000000..37bb67189
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_00.obj
@@ -0,0 +1,25123 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link3_00.mtl
+o link3_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.obj
new file mode 100644
index 000000000..764f4c791
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_01.obj
@@ -0,0 +1,4799 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link3_01.mtl
+o link3_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.obj
new file mode 100644
index 000000000..6e1482455
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link3_02.obj
@@ -0,0 +1,2085 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link3_02.mtl
+o link3_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
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+Ni 1.500000
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.obj
new file mode 100644
index 000000000..d08e04a54
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_00.obj
@@ -0,0 +1,24102 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link4_00.mtl
+o link4_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.obj
new file mode 100644
index 000000000..0e0c12149
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_01.obj
@@ -0,0 +1,1879 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link4_01.mtl
+o link4_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.obj
new file mode 100644
index 000000000..949305623
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link4_02.obj
@@ -0,0 +1,3095 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link4_02.mtl
+o link4_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.obj
new file mode 100644
index 000000000..9207f9c9a
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_00.obj
@@ -0,0 +1,25599 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link5_00.mtl
+o link5_00
+v 0.017487 0.017200 -0.044830
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.obj
new file mode 100644
index 000000000..ef383c43a
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_01.obj
@@ -0,0 +1,1815 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link5_01.mtl
+o link5_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.obj
new file mode 100644
index 000000000..4a1c83371
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link5_02.obj
@@ -0,0 +1,4726 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link5_02.mtl
+o link5_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.obj
new file mode 100644
index 000000000..bc3c97308
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_00.obj
@@ -0,0 +1,7326 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link6_00.mtl
+o link6_00
+v 0.020500 -0.017487 0.000670
+v 0.020500 0.017384 -0.002008
+v 0.019000 -0.005280 0.016684
+v 0.019000 -0.010068 0.014314
+v 0.019000 -0.013918 0.010609
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.obj
new file mode 100644
index 000000000..d7030b3f6
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_01.obj
@@ -0,0 +1,3242 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link6_01.mtl
+o link6_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.obj
new file mode 100644
index 000000000..e22fe7503
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/arm/link6_02.obj
@@ -0,0 +1,3315 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib link6_02.mtl
+o link6_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0.stl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0.stl
new file mode 100644
index 000000000..fc9401a70
Binary files /dev/null and b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0.stl differ
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0_5.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0_5.obj
new file mode 100644
index 000000000..79a13c478
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/body/body_link0_5.obj
@@ -0,0 +1,91158 @@
+# Copyright 2026 Enactic, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/cell.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/cell.obj
new file mode 100644
index 000000000..3cfefc570
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/cell.obj
@@ -0,0 +1,6409 @@
+# WaveFront *.obj file (generated by Autodesk ATF)
+
+mtllib OpenEvalCell_onepiece.mtl
+
+g Body1
+
+v 52.000000 6.000000 124.550300
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+
+# 1 groups
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/sheet.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/sheet.obj
new file mode 100644
index 000000000..e67b407e7
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/cell/sheet.obj
@@ -0,0 +1,781 @@
+# Copyright 2026 Enactic, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# WaveFront *.obj file (generated by Autodesk ATF)
+
+mtllib whiteSheet.mtl
+
+g Body1
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+# 190 texture params
+# 190 normals
+# 248 facets
+
+# 1 groups
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.obj
new file mode 100644
index 000000000..7819835ea
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_00.obj
@@ -0,0 +1,50506 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib ee_base_link_00.mtl
+o ee_base_link_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.mtl
new file mode 100644
index 000000000..f92d7dd91
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl metal_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.650000 0.650000 0.650000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.obj
new file mode 100644
index 000000000..148a61321
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_01.obj
@@ -0,0 +1,1248 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib ee_base_link_01.mtl
+o ee_base_link_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.obj
new file mode 100644
index 000000000..86267e0e1
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/ee_base_link_02.obj
@@ -0,0 +1,8603 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib ee_base_link_02.mtl
+o ee_base_link_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.obj
new file mode 100644
index 000000000..d43ffdc38
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_00.obj
@@ -0,0 +1,4320 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_inner_00.mtl
+o finger_inner_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.obj
new file mode 100644
index 000000000..9222abf85
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_01.obj
@@ -0,0 +1,6012 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_inner_01.mtl
+o finger_inner_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.obj
new file mode 100644
index 000000000..eeb7a8e32
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_inner_02.obj
@@ -0,0 +1,2388 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_inner_02.mtl
+o finger_inner_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.obj
new file mode 100644
index 000000000..be291eac5
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_00.obj
@@ -0,0 +1,4330 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_outer_00.mtl
+o finger_outer_00
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.mtl
new file mode 100644
index 000000000..a6aaee531
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl matte_black
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.247000 0.247000 0.247000
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.obj
new file mode 100644
index 000000000..24e8f60b3
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_01.obj
@@ -0,0 +1,6046 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_outer_01.mtl
+o finger_outer_01
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.mtl b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.mtl
new file mode 100644
index 000000000..fd29d0202
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.mtl
@@ -0,0 +1,12 @@
+# Blender 4.3.2 MTL File: 'None'
+# www.blender.org
+
+newmtl pale_silver
+Ns 250.000000
+Ka 1.000000 1.000000 1.000000
+Kd 0.752941 0.752941 0.752941
+Ks 0.500000 0.500000 0.500000
+Ke 0.000000 0.000000 0.000000
+Ni 1.500000
+d 1.000000
+illum 2
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.obj b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.obj
new file mode 100644
index 000000000..e19627516
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/assets/visual/gripper/finger_outer_02.obj
@@ -0,0 +1,2423 @@
+# Blender 4.3.2
+# www.blender.org
+mtllib finger_outer_02.mtl
+o finger_outer_02
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diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/cell.xml b/src/unilab/assets/robots/openarm_mujoco_v2/cell.xml
new file mode 100644
index 000000000..6ae713a62
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/cell.xml
@@ -0,0 +1,105 @@
+<!--
+Copyright 2026 Enactic, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<mujoco>
+  <compiler meshdir="assets" angle="radian"/>
+
+  <default>
+    <default class="visual">
+      <geom contype="0" conaffinity="0" group="2" />
+    </default>
+    <default class="cell_collision">
+      <geom material="collision_material" condim="3" contype="1" conaffinity="1" priority="1" group="4" solref="0.005 1" friction="1 0.005 0.001" />
+      <equality solimp="0.99 0.999 1e-05" solref="0.005 1" />
+    </default>
+    <default class="cell_visual">
+      <geom contype="0" conaffinity="0" group="1" />
+    </default>
+    <default class="lifter">
+      <joint limited="true" type="slide" damping="50" />
+    </default>
+    <default class="position_lifter">
+      <position kp="8000" kv="4000" forcelimited="true" forcerange="-3000 3000" />
+    </default>
+  </default>
+
+  <statistic center="1.3 0 0.6" extent="3.5" meansize="0.05"/>
+  <option timestep="0.001" />
+
+  <visual>
+    <headlight diffuse="0.6 0.6 0.6" ambient="0.3 0.3 0.3" specular="0 0 0"/>
+    <rgba haze="0.15 0.25 0.35 1"/>
+    <global azimuth="0" elevation="-20"/>
+    <quality shadowsize="8192"/>
+  </visual>
+
+  <asset>
+    <texture type="skybox" builtin="gradient" rgb1="0.3 0.5 0.7" rgb2="0 0 0" width="512" height="3072"/>
+    <texture type="2d" name="groundplane" builtin="checker" mark="edge" rgb1="0.2 0.3 0.4" rgb2="0.1 0.2 0.3"
+      markrgb="0.8 0.8 0.8" width="300" height="300"/>
+    <material name="groundplane"    texture="groundplane" texuniform="true" texrepeat="5 5" reflectance="0.2"/>
+    <material name="cell_matte_black"    rgba="0.247 0.247 0.247 1.0" reflectance="0.05" shininess="0.5"/>
+    <material name="cell_matte_offwhite" rgba="0.95 0.94 0.90 1"      reflectance="0.05" shininess="0.1"/>
+    <mesh name="cell_mesh"    file="visual/cell/cell.obj"   scale="0.01  0.01  0.01"/>
+    <mesh name="sheet_mesh"   file="visual/cell/sheet.obj"  scale="0.01  0.01  0.01"/>
+    <model name="bimanual" file="openarm_bimanual.xml"/>
+  </asset>
+
+  <actuator>
+    <position name="lifter_ctrl" joint="openarm_lifter_joint" class="position_lifter"
+              kp="8000" kv="4000" ctrllimited="true" ctrlrange="0 0.3"/>
+  </actuator>
+
+  <worldbody>
+
+    <light pos="0 0 1.5" dir="0 0 -1" directional="true"/>
+
+    <geom name="floor" size="0 0 0.05" type="plane" material="groundplane"/>
+
+    <geom name="cell_vis" type="mesh" mesh="cell_mesh"  pos="0 0.550 0"      euler="0 0 -1.5708" material="cell_matte_black"    class="cell_visual" group="3"/>
+    <geom name="sheet"    type="mesh" mesh="sheet_mesh" pos="0.4225 0 1.005" euler="0 0 -1.5708" material="cell_matte_offwhite" class="cell_visual"/>
+
+    <geom name="cell_table_col"      type="box" pos="0.41 0 1.00"    size="0.41 0.55 0.005" class="cell_collision"/>
+    <geom name="cell_left_wall_col"  type="box" pos="0.43 0.52 1.42" size="0.43 0.03 0.42"  class="cell_collision"/>
+    <geom name="cell_right_wall_col" type="box" pos="0.43 -0.52 1.42" size="0.43 0.03 0.42" class="cell_collision"/>
+    <geom name="cell_front_wall_col" type="box" pos="0.85 0 1.42"    size="0.03 0.49 0.42"  class="cell_collision"/>
+    <geom name="cell_roof_col"       type="box" pos="0.41 0 1.82"    size="0.41 0.55 0.005" class="cell_collision"/>
+    <geom name="cell_rail_col1"       type="box" pos="0.03 0 1.525"   size="0.03 0.03 0.3"  class="cell_collision"/>
+    <geom name="cell_rail_col2"       type="box" pos="0.0915 0 1.535"   size="0.0315 0.039 0.29"  class="cell_collision"/>
+    <!-- <geom name="cell_rail_col"       type="box" pos="0.058 0 1.55"   size="0.003 0.03 0.3"  class="cell_collision"/> -->
+
+    <camera name="camera_ceiling" pos="0.245 0 1.8" xyaxes="0 -1 0 1 0 0"    fovy="66" resolution="960 600"/>
+    <!-- need to adjust x after lifter link is adjusted -->
+    <camera name="camera_head_left"    pos="0.223 -0.0315 1.45"  xyaxes="0 -1 0 0.882948 0 0.469472" fovy="52" resolution="1280 720"/>
+    <camera name="camera_head_right"    pos="0.223 0.0315 1.45"  xyaxes="0 -1 0 0.882948 0 0.469472" fovy="52" resolution="1280 720"/>
+
+    <!-- lifter body: arms attach here and slide vertically -->
+    <body name="openarm_lifter_link" pos="0.185 0 1.34">
+      <geom name="body_lifter" type="box" pos="-0.01575 0 0"   size="0.04575 0.031 0.061"  material="cell_matte_black" class="cell_visual"/>
+      <geom name="body_lifter_col" type="box" pos="-0.01575 0 0"   size="0.04575 0.031 0.061"  class="cell_collision"/>
+      <inertial pos="0 0 0" mass="5.0" diaginertia="0.1 0.1 0.1"/>
+      <joint name="openarm_lifter_joint" class="lifter" axis="0 0 1" range="0 0.3"/>
+      <attach model="bimanual" prefix=""/>
+    </body>
+
+  </worldbody>
+  <keyframe>
+    <key name="home"
+      qpos="0.0
+            0.0 0.0 0.0 1.570796 0.0 0.0 0.0 0.0 0.0
+            0.0 0.0 0.0 1.570796 0.0 0.0 0.0 0.0 0.0" />
+  </keyframe>
+</mujoco>
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/demo.xml b/src/unilab/assets/robots/openarm_mujoco_v2/demo.xml
new file mode 100644
index 000000000..1b781c545
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/demo.xml
@@ -0,0 +1,43 @@
+<!--
+Copyright 2026 Enactic, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<mujoco model="openarm_bimanual cell demo">
+  <visual>
+    <global offwidth="960" offheight="600"/>
+  </visual>
+
+  <asset>
+    <model name="cell" file="cell.xml"/>
+  </asset>
+  <worldbody>
+    <attach model="cell" prefix=""/>
+
+    <body name="orange_cube" pos="0.45 0.0 1.05">
+      <freejoint/>
+      <geom type="box" size="0.02 0.02 0.02" rgba="1.0 0.4 0.0 1"
+            mass="0.05" friction="1 0.5 0.01" contype="1" conaffinity="1"/>
+    </body>
+
+    <body name="black_frame" pos="0.47 0.15 1.005">
+      <geom type="box" pos="0 0 0.005"    size="0.07 0.07 0.005" rgba="0.1 0.1 0.1 1" contype="1" conaffinity="1"/>
+      <geom type="box" pos="0.065 0 0.02"  size="0.005 0.07 0.02" rgba="0.1 0.1 0.1 1" contype="1" conaffinity="1"/>
+      <geom type="box" pos="-0.065 0 0.02" size="0.005 0.07 0.02" rgba="0.1 0.1 0.1 1" contype="1" conaffinity="1"/>
+      <geom type="box" pos="0 0.065 0.02"  size="0.06 0.005 0.02" rgba="0.1 0.1 0.1 1" contype="1" conaffinity="1"/>
+      <geom type="box" pos="0 -0.065 0.02" size="0.06 0.005 0.02" rgba="0.1 0.1 0.1 1" contype="1" conaffinity="1"/>
+    </body>
+  </worldbody>
+
+</mujoco>
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/demo_lift3d.xml b/src/unilab/assets/robots/openarm_mujoco_v2/demo_lift3d.xml
new file mode 100644
index 000000000..2df1f976d
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/demo_lift3d.xml
@@ -0,0 +1,43 @@
+<!--
+Copyright 2026 Enactic, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<!--
+  Graspability-tuned scene (lift3d variants point here via env.scene.model_file):
+    * cube 0.04 m -> 0.03 m (half-size 0.015) so the parallel jaws can fully close around it,
+    * higher cube friction (sliding 2.0, torsional 0.5, rolling 0.05) to resist slip on carry,
+    * remove the static black_frame distractor under the gripper home.
+  Everything else matches demo.xml; the "home" keyframe is inherited from the attached cell model.
+-->
+
+<mujoco model="openarm_bimanual cell demo (lift3d)">
+  <visual>
+    <global offwidth="960" offheight="600"/>
+  </visual>
+
+  <asset>
+    <model name="cell" file="cell.xml"/>
+  </asset>
+  <worldbody>
+    <attach model="cell" prefix=""/>
+
+    <body name="orange_cube" pos="0.45 0.0 1.05">
+      <freejoint/>
+      <geom type="box" size="0.015 0.015 0.015" rgba="1.0 0.4 0.0 1"
+            mass="0.04" friction="2.0 0.5 0.05" contype="1" conaffinity="1"/>
+    </body>
+  </worldbody>
+
+</mujoco>
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/openarm_bimanual.xml b/src/unilab/assets/robots/openarm_mujoco_v2/openarm_bimanual.xml
new file mode 100644
index 000000000..f6aede8f3
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/openarm_bimanual.xml
@@ -0,0 +1,379 @@
+<?xml version='1.0' encoding='utf-8'?>
+<!--
+Copyright 2026 Enactic, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<mujoco model="openarm_v20">
+  <default>
+    <joint stiffness="0" ref="0.0" />
+    <default class="robot">
+      <default class="motor_DM8009">
+        <joint frictionloss="0.2" damping="1.0" armature="0.0081" limited="true" type="hinge" />
+        <motor forcelimited="true" forcerange="-40 40" />
+      </default>
+      <default class="motor_DM4340">
+        <joint frictionloss="0.1" damping="0.9" armature="0.1600" limited="true" type="hinge" />
+        <motor forcelimited="true" forcerange="-27 27" />
+      </default>
+      <default class="motor_DM4310">
+        <joint frictionloss="0.04" damping="0.9" armature="0.0100" limited="true" type="hinge" />
+        <motor forcelimited="true" forcerange="-7 7" />
+      </default>
+      <default class="motor_DM3507">
+        <joint frictionloss="0.01" damping="0.01" armature="0.0049" limited="true" type="hinge" />
+        <motor forcelimited="true" forcerange="-7 7" />
+      </default>
+      <default class="motor_finger">
+        <joint limited="true" type="hinge" damping="2" />
+        <position forcelimited="true" forcerange="-333 333" ctrllimited="true" ctrlrange="0 0.7854" />
+      </default>
+      <default class="lifter">
+        <joint limited="true" type="slide" damping="50" />
+        <position forcelimited="true" forcerange="-3000 3000" ctrllimited="true" ctrlrange="0 0.3" />
+      </default>
+      <default class="position_DM8009">
+        <position kp="200" kv="150" forcelimited="true" forcerange="-40 40" />
+      </default>
+      <default class="position_DM4340">
+        <position kp="100" kv="30" forcelimited="true" forcerange="-27 27" />
+      </default>
+      <default class="position_DM4310">
+        <position kp="200" kv="5" forcelimited="true" forcerange="-7 7" />
+      </default>
+      <default class="position_DM3507">
+        <position kp="200" kv="5" forcelimited="true" forcerange="-7 7" />
+      </default>
+      <default class="position_lifter">
+        <position kp="8000" kv="4000" forcelimited="true" forcerange="-3000 3000" />
+      </default>
+      <default class="collision">
+        <geom material="collision_material" condim="3" conaffinity="1" priority="1" group="3" solref="0.005 1" friction="1 0.01 0.01" />
+        <equality solimp="0.99 0.999 1e-05" solref="0.005 1" />
+      </default>
+      <default class="visual">
+        <geom material="visualgeom" contype="0" conaffinity="0" group="2" />
+      </default>
+    </default>
+  </default>
+  <compiler angle="radian" meshdir="assets" />
+  <asset>
+    <material name="collision_material" rgba="0.8 0.2 0.2 0.5" />
+    <material name="visualgeom" rgba="0.7 0.7 0.7 1" />
+    <material name="pale_silver" rgba="0.752941 0.752941 0.752941 1" specular="1.0" shininess="0.9" reflectance="0.8" />
+    <material name="metal_silver" rgba="0.65 0.65 0.65 1.0" specular="1.0" shininess="0.9" reflectance="0.8" />
+    <material name="matte_black" rgba="0.247 0.247 0.247 1.0" reflectance="0.05" shininess="0.5" />
+
+    <mesh name="base_link_left_00" content_type="model/obj" file="visual/arm/base_link_00.obj" scale="1 -1 1" />
+    <mesh name="base_link_left_01" content_type="model/obj" file="visual/arm/base_link_01.obj" scale="1 -1 1" />
+    <mesh name="base_link_left_collision_00" content_type="model/stl" file="collision/base_link.stl" scale="1 -1 1" />
+    <mesh name="link1_left_00" content_type="model/obj" file="visual/arm/link1_00.obj" scale="1 -1 1" />
+    <mesh name="link1_left_01" content_type="model/obj" file="visual/arm/link1_01.obj" scale="1 -1 1" />
+    <mesh name="link1_left_02" content_type="model/obj" file="visual/arm/link1_02.obj" scale="1 -1 1" />
+    <mesh name="link1_left_collision_00" content_type="model/stl" file="collision/link1.stl" scale="1 -1 1" />
+    <mesh name="link2_left_00" content_type="model/obj" file="visual/arm/link2_00.obj" scale="1 -1 1" />
+    <mesh name="link2_left_01" content_type="model/obj" file="visual/arm/link2_01.obj" scale="1 -1 1" />
+    <mesh name="link2_left_02" content_type="model/obj" file="visual/arm/link2_02.obj" scale="1 -1 1" />
+    <mesh name="link2_left_collision_00" content_type="model/stl" file="collision/link2.stl" scale="1 -1 1" />
+    <mesh name="link3_left_00" content_type="model/obj" file="visual/arm/link3_00.obj" />
+    <mesh name="link3_left_01" content_type="model/obj" file="visual/arm/link3_01.obj" />
+    <mesh name="link3_left_02" content_type="model/obj" file="visual/arm/link3_02.obj" />
+    <mesh name="link3_left_collision_00" content_type="model/stl" file="collision/link3.stl" />
+    <mesh name="link4_left_00" content_type="model/obj" file="visual/arm/link4_00.obj" />
+    <mesh name="link4_left_01" content_type="model/obj" file="visual/arm/link4_01.obj" />
+    <mesh name="link4_left_02" content_type="model/obj" file="visual/arm/link4_02.obj" />
+    <mesh name="link4_left_collision_00" content_type="model/stl" file="collision/link4.stl" />
+    <mesh name="link5_left_00" content_type="model/obj" file="visual/arm/link5_00.obj" scale="1 -1 1" />
+    <mesh name="link5_left_01" content_type="model/obj" file="visual/arm/link5_01.obj" scale="1 -1 1" />
+    <mesh name="link5_left_02" content_type="model/obj" file="visual/arm/link5_02.obj" scale="1 -1 1" />
+    <mesh name="link5_left_collision_00" content_type="model/stl" file="collision/link5_part_00.stl" scale="1 -1 1" />
+    <mesh name="link5_left_collision_01" content_type="model/stl" file="collision/link5_part_01.stl" scale="1 -1 1" />
+    <mesh name="link5_left_collision_02" content_type="model/stl" file="collision/link5_part_02.stl" scale="1 -1 1" />
+    <mesh name="link6_left_00" content_type="model/obj" file="visual/arm/link6_00.obj" scale="1 -1 1" />
+    <mesh name="link6_left_01" content_type="model/obj" file="visual/arm/link6_01.obj" scale="1 -1 1" />
+    <mesh name="link6_left_02" content_type="model/obj" file="visual/arm/link6_02.obj" scale="1 -1 1" />
+    <mesh name="link6_left_collision_00" content_type="model/stl" file="collision/link6.stl" scale="1 -1 1" />
+    <mesh name="ee_base_link_left_00" content_type="model/obj" file="visual/gripper/ee_base_link_00.obj" scale="1 -1 1" />
+    <mesh name="ee_base_link_left_01" content_type="model/obj" file="visual/gripper/ee_base_link_01.obj" scale="1 -1 1" />
+    <mesh name="ee_base_link_left_02" content_type="model/obj" file="visual/gripper/ee_base_link_02.obj" scale="1 -1 1" />
+    <mesh name="ee_base_link_left_collision_00" content_type="model/stl" file="collision/ee_base_link.stl" scale="1 -1 1" />
+    <mesh name="finger_inner_left_00" content_type="model/obj" file="visual/gripper/finger_inner_00.obj" scale="1 -1 1" />
+    <mesh name="finger_inner_left_01" content_type="model/obj" file="visual/gripper/finger_inner_01.obj" scale="1 -1 1" />
+    <mesh name="finger_inner_left_02" content_type="model/obj" file="visual/gripper/finger_inner_02.obj" scale="1 -1 1" />
+    <mesh name="finger_inner_left_collision_00" content_type="model/stl" file="collision/finger_inner_part_00.stl" scale="1 -1 1" />
+    <mesh name="finger_inner_left_collision_01" content_type="model/stl" file="collision/finger_inner_part_01.stl" scale="1 -1 1" />
+    <mesh name="finger_inner_left_collision_02" content_type="model/stl" file="collision/finger_inner_part_02.stl" scale="1 -1 1" />
+    <mesh name="finger_inner_left_collision_03" content_type="model/stl" file="collision/finger_inner_part_03.stl" scale="1 -1 1" />
+    <mesh name="finger_outer_left_00" content_type="model/obj" file="visual/gripper/finger_outer_00.obj" scale="1 -1 1" />
+    <mesh name="finger_outer_left_01" content_type="model/obj" file="visual/gripper/finger_outer_01.obj" scale="1 -1 1" />
+    <mesh name="finger_outer_left_02" content_type="model/obj" file="visual/gripper/finger_outer_02.obj" scale="1 -1 1" />
+    <mesh name="finger_outer_left_collision_00" content_type="model/stl" file="collision/finger_outer_part_00.stl" scale="1 -1 1" />
+    <mesh name="finger_outer_left_collision_01" content_type="model/stl" file="collision/finger_outer_part_01.stl" scale="1 -1 1" />
+    <mesh name="finger_outer_left_collision_02" content_type="model/stl" file="collision/finger_outer_part_02.stl" scale="1 -1 1" />
+    <mesh name="finger_outer_left_collision_03" content_type="model/stl" file="collision/finger_outer_part_03.stl" scale="1 -1 1" />
+    <mesh name="base_link_right_00" content_type="model/obj" file="visual/arm/base_link_00.obj" />
+    <mesh name="base_link_right_01" content_type="model/obj" file="visual/arm/base_link_01.obj" />
+    <mesh name="base_link_right_collision_00" content_type="model/stl" file="collision/base_link.stl" />
+    <mesh name="link1_right_00" content_type="model/obj" file="visual/arm/link1_00.obj" />
+    <mesh name="link1_right_01" content_type="model/obj" file="visual/arm/link1_01.obj" />
+    <mesh name="link1_right_02" content_type="model/obj" file="visual/arm/link1_02.obj" />
+    <mesh name="link1_right_collision_00" content_type="model/stl" file="collision/link1.stl" />
+    <mesh name="link2_right_00" content_type="model/obj" file="visual/arm/link2_00.obj" />
+    <mesh name="link2_right_01" content_type="model/obj" file="visual/arm/link2_01.obj" />
+    <mesh name="link2_right_02" content_type="model/obj" file="visual/arm/link2_02.obj" />
+    <mesh name="link2_right_collision_00" content_type="model/stl" file="collision/link2.stl" />
+    <mesh name="link3_right_00" content_type="model/obj" file="visual/arm/link3_00.obj" />
+    <mesh name="link3_right_01" content_type="model/obj" file="visual/arm/link3_01.obj" />
+    <mesh name="link3_right_02" content_type="model/obj" file="visual/arm/link3_02.obj" />
+    <mesh name="link3_right_collision_00" content_type="model/stl" file="collision/link3.stl" />
+    <mesh name="link4_right_00" content_type="model/obj" file="visual/arm/link4_00.obj" />
+    <mesh name="link4_right_01" content_type="model/obj" file="visual/arm/link4_01.obj" />
+    <mesh name="link4_right_02" content_type="model/obj" file="visual/arm/link4_02.obj" />
+    <mesh name="link4_right_collision_00" content_type="model/stl" file="collision/link4.stl" />
+    <mesh name="link5_right_00" content_type="model/obj" file="visual/arm/link5_00.obj" />
+    <mesh name="link5_right_01" content_type="model/obj" file="visual/arm/link5_01.obj" />
+    <mesh name="link5_right_02" content_type="model/obj" file="visual/arm/link5_02.obj" />
+    <mesh name="link5_right_collision_00" content_type="model/stl" file="collision/link5_part_00.stl" />
+    <mesh name="link5_right_collision_01" content_type="model/stl" file="collision/link5_part_01.stl" />
+    <mesh name="link5_right_collision_02" content_type="model/stl" file="collision/link5_part_02.stl" />
+    <mesh name="link6_right_00" content_type="model/obj" file="visual/arm/link6_00.obj" />
+    <mesh name="link6_right_01" content_type="model/obj" file="visual/arm/link6_01.obj" />
+    <mesh name="link6_right_02" content_type="model/obj" file="visual/arm/link6_02.obj" />
+    <mesh name="link6_right_collision_00" content_type="model/stl" file="collision/link6.stl" />
+    <mesh name="ee_base_link_right_00" content_type="model/obj" file="visual/gripper/ee_base_link_00.obj" />
+    <mesh name="ee_base_link_right_01" content_type="model/obj" file="visual/gripper/ee_base_link_01.obj" />
+    <mesh name="ee_base_link_right_02" content_type="model/obj" file="visual/gripper/ee_base_link_02.obj" />
+    <mesh name="ee_base_link_right_collision_00" content_type="model/stl" file="collision/ee_base_link.stl" />
+    <mesh name="finger_inner_right_00" content_type="model/obj" file="visual/gripper/finger_inner_00.obj" />
+    <mesh name="finger_inner_right_01" content_type="model/obj" file="visual/gripper/finger_inner_01.obj" />
+    <mesh name="finger_inner_right_02" content_type="model/obj" file="visual/gripper/finger_inner_02.obj" />
+    <mesh name="finger_inner_right_collision_00" content_type="model/stl" file="collision/finger_inner_part_00.stl" />
+    <mesh name="finger_inner_right_collision_01" content_type="model/stl" file="collision/finger_inner_part_01.stl" />
+    <mesh name="finger_inner_right_collision_02" content_type="model/stl" file="collision/finger_inner_part_02.stl" />
+    <mesh name="finger_inner_right_collision_03" content_type="model/stl" file="collision/finger_inner_part_03.stl" />
+    <mesh name="finger_outer_right_00" content_type="model/obj" file="visual/gripper/finger_outer_00.obj" />
+    <mesh name="finger_outer_right_01" content_type="model/obj" file="visual/gripper/finger_outer_01.obj" />
+    <mesh name="finger_outer_right_02" content_type="model/obj" file="visual/gripper/finger_outer_02.obj" />
+    <mesh name="finger_outer_right_collision_00" content_type="model/stl" file="collision/finger_outer_part_00.stl" />
+    <mesh name="finger_outer_right_collision_01" content_type="model/stl" file="collision/finger_outer_part_01.stl" />
+    <mesh name="finger_outer_right_collision_02" content_type="model/stl" file="collision/finger_outer_part_02.stl" />
+    <mesh name="finger_outer_right_collision_03" content_type="model/stl" file="collision/finger_outer_part_03.stl" />
+  </asset>
+  <worldbody>
+    <body name="openarm_left_base_link" pos="0 0.031 0">
+      <inertial pos="-0.00253124 0.0258186 -2.70658e-05" quat="-1.46856942085e-06 0.70739772103 0.706815721259 2.1457591538e-05" mass="1.14323" diaginertia="0.00159935 0.00113608 0.000750542" />
+      <geom name="base_link_left_00" type="mesh" mesh="base_link_left_00" class="visual" material="matte_black" quat="0 0 1 0" />
+      <geom name="base_link_left_01" type="mesh" mesh="base_link_left_01" class="visual" material="pale_silver" quat="0 0 1 0" />
+      <geom name="base_link_left_collision_00" type="mesh" mesh="base_link_left_collision_00" class="collision" quat="0 0 1 0" />
+      <body name="openarm_left_link1" pos="0 0.0625 0">
+        <inertial pos="0.00090035 0.044466 2.88441e-05" quat="0.999901 -0.000371041 -5.04627e-05 -0.0140338" mass="1.14167" diaginertia="0.00109459 0.000758935 0.000670659" />
+        <joint name="openarm_left_joint1" pos="0 0 0" axis="0 1 0" range="-3.4907 1.3963" actuatorfrcrange="-40 40" class="motor_DM8009" />
+        <geom name="link1_left_00" type="mesh" mesh="link1_left_00" class="visual" material="matte_black" />
+        <geom name="link1_left_01" type="mesh" mesh="link1_left_01" class="visual" material="pale_silver" />
+        <geom name="link1_left_02" type="mesh" mesh="link1_left_02" class="visual" material="metal_silver" />
+        <geom name="link1_left_collision_00" type="mesh" mesh="link1_left_collision_00" class="collision" />
+        <body name="openarm_left_link2" pos="0 0.06 0">
+          <inertial pos="-0.0247185 -7.60578e-08 -0.0312643" quat="0.999342 -6.47495e-06 -0.0362804 3.02331e-06" mass="0.277509" diaginertia="0.000153968 0.000113062 8.19211e-05" />
+          <joint name="openarm_left_joint2" pos="0 0 0" axis="-1 0 0" range="-3.3161 0.17453" actuatorfrcrange="-40 40" class="motor_DM8009" />
+          <geom name="link2_left_00" type="mesh" mesh="link2_left_00" class="visual" material="matte_black" />
+          <geom name="link2_left_01" type="mesh" mesh="link2_left_01" class="visual" material="metal_silver" />
+          <geom name="link2_left_02" type="mesh" mesh="link2_left_02" class="visual" material="pale_silver" />
+          <geom name="link2_left_collision_00" type="mesh" mesh="link2_left_collision_00" class="collision" />
+          <body name="openarm_left_link3" pos="0 0 -0.06625">
+            <inertial pos="-0.00300862 -0.000514813 -0.109368" quat="0.998906 -0.00891348 0.0458105 0.00280505" mass="1.07386" diaginertia="0.00129561 0.00114038 0.000553361" />
+            <joint name="openarm_left_joint3" pos="0 0 0" axis="0 0 -1" range="-1.5708 1.5708" actuatorfrcrange="-27 27" class="motor_DM4340" />
+            <geom name="link3_left_00" type="mesh" mesh="link3_left_00" class="visual" material="matte_black" />
+            <geom name="link3_left_01" type="mesh" mesh="link3_left_01" class="visual" material="metal_silver" />
+            <geom name="link3_left_02" type="mesh" mesh="link3_left_02" class="visual" material="pale_silver" />
+            <geom name="link3_left_collision_00" type="mesh" mesh="link3_left_collision_00" class="collision" />
+            <body name="openarm_left_link4" pos="0 0 -0.15375">
+              <inertial pos="-0.00310326 -0.00136539 -0.0574601" quat="0.996952 0.00947325 0.00348083 0.0773554" mass="0.634853" diaginertia="0.000469894 0.000433114 0.000245134" />
+              <joint name="openarm_left_joint4" pos="0 0 0" axis="0 -1 0" range="0 2.4435" actuatorfrcrange="-27 27" class="motor_DM4340" />
+              <geom name="link4_left_00" type="mesh" mesh="link4_left_00" class="visual" material="matte_black" />
+              <geom name="link4_left_01" type="mesh" mesh="link4_left_01" class="visual" material="pale_silver" />
+              <geom name="link4_left_02" type="mesh" mesh="link4_left_02" class="visual" material="metal_silver" />
+              <geom name="link4_left_collision_00" type="mesh" mesh="link4_left_collision_00" class="collision" />
+              <body name="openarm_left_link5" pos="0 0 -0.0955">
+                <inertial pos="-0.000737189 0.000412407 -0.0470938" quat="0.685547 -0.0023482 -0.00297125 0.728019" mass="0.615659" diaginertia="0.000334799 0.00027946 0.000176657" />
+                <joint name="openarm_left_joint5" pos="0 0 0" axis="0 0 -1" range="-1.5708 1.5708" actuatorfrcrange="-7 7" class="motor_DM4310" />
+                <geom name="link5_left_00" type="mesh" mesh="link5_left_00" class="visual" material="matte_black" />
+                <geom name="link5_left_01" type="mesh" mesh="link5_left_01" class="visual" material="pale_silver" />
+                <geom name="link5_left_02" type="mesh" mesh="link5_left_02" class="visual" material="metal_silver" />
+                <geom name="link5_left_collision_00" type="mesh" mesh="link5_left_collision_00" class="collision" />
+                <geom name="link5_left_collision_01" type="mesh" mesh="link5_left_collision_01" class="collision" />
+                <geom name="link5_left_collision_02" type="mesh" mesh="link5_left_collision_02" class="collision" />
+                <body name="openarm_left_link6" pos="0 0 -0.1205">
+                  <inertial pos="2.27438e-05 -0.000686496 5.44e-05" quat="0.999832 -0.0183155 0.000397003 -0.000757974" mass="0.475203" diaginertia="0.000179276 0.000136249 0.000135339" />
+                  <joint name="openarm_left_joint6" pos="0 0 0" axis="0 -1 0" range="-0.7854 0.7854" actuatorfrcrange="-7 7" class="motor_DM4310" />
+                  <geom name="link6_left_00" type="mesh" mesh="link6_left_00" class="visual" material="matte_black" />
+                  <geom name="link6_left_01" type="mesh" mesh="link6_left_01" class="visual" material="metal_silver" />
+                  <geom name="link6_left_02" type="mesh" mesh="link6_left_02" class="visual" material="pale_silver" />
+                  <geom name="link6_left_collision_00" type="mesh" mesh="link6_left_collision_00" class="collision" />
+                  <body name="openarm_left_ee_base_link">
+                    <inertial pos="0.0137902 -0.0084073 -0.05938" quat="0.760121 0.648846 -0.0304587 -0.0169317" mass="0.52832" diaginertia="0.000219417 0.000166122 0.000155742" />
+                    <joint name="openarm_left_joint7" pos="0 0 0" axis="1 0 0" range="-1.5708 1.5708" actuatorfrcrange="-7 7" class="motor_DM3507" />
+                    <geom name="ee_base_link_left_00" pos="0.0205 0 0" quat="1 0 0 0" type="mesh" mesh="ee_base_link_left_00" class="visual" material="matte_black" />
+                    <geom name="ee_base_link_left_01" pos="0.0205 0 0" type="mesh" mesh="ee_base_link_left_01" class="visual" material="metal_silver" />
+                    <geom name="ee_base_link_left_02" pos="0.0205 0 0" type="mesh" mesh="ee_base_link_left_02" class="visual" material="pale_silver" />
+                    <geom name="ee_base_link_left_collision_00" pos="0.0205 0 0" quat="1 0 0 0" type="mesh" mesh="ee_base_link_left_collision_00" class="collision" />
+                    <camera name="camera_wrist_left" pos="0.023 0.0182 -0.10236" euler="-0.366519 0.22689 -1.5708" fovy="66" resolution="960 600"/>
+                    <site name="left_ee_control_point" pos="0 0 0.0" size="0.01" rgba="0 1 0 1" />
+                    <!-- Grasp-point reference frame between the jaws (fingers at z=-0.068 + tip extent),
+                         used by the scripted IK pick controller. Invisible (alpha 0). -->
+                    <site name="openarm_left_tcp" pos="-0.004 0 -0.135" size="0.005" rgba="0 0 0 0" />
+                    <body name="openarm_left_ee_inner_finger" pos="-0.00143 -0.018 -0.068">
+                      <inertial pos="-0.0124991 -0.00176593 -0.0241663" quat="0.982638 0.0922084 -0.15927 -0.0235197" mass="0.125979" diaginertia="3.8543e-05 3.6883e-05 1.43942e-05" />
+                      <joint name="openarm_left_finger_joint1" pos="0 0 0" axis="-1 0 0" range="0 0.7854" actuatorfrcrange="-10 10" class="motor_finger" />
+                      <geom name="finger_inner_left_00" type="mesh" mesh="finger_inner_left_00" class="visual" material="matte_black" />
+                      <geom name="finger_inner_left_01" type="mesh" mesh="finger_inner_left_01" class="visual" material="matte_black" />
+                      <geom name="finger_inner_left_02" type="mesh" mesh="finger_inner_left_02" class="visual" material="pale_silver" />
+                      <geom name="finger_inner_left_collision_00" type="mesh" mesh="finger_inner_left_collision_00" class="collision" />
+                      <geom name="finger_inner_left_collision_01" type="mesh" mesh="finger_inner_left_collision_01" class="collision" />
+                      <geom name="finger_inner_left_collision_02" type="mesh" mesh="finger_inner_left_collision_02" class="collision" />
+                      <geom name="finger_inner_left_collision_03" type="mesh" mesh="finger_inner_left_collision_03" class="collision" />
+                    </body>
+                    <body name="openarm_left_ee_outer_finger" pos="-0.00143 0.018 -0.068">
+                      <inertial pos="-0.012796 0.0020183 -0.026792" quat="0.982097 -0.0906989 -0.165079 0.00294117" mass="0.11372" diaginertia="3.70662e-05 3.60159e-05 1.33599e-05" />
+                      <joint name="openarm_left_finger_joint2" pos="0 0 0" axis="1 0 0" range="0 0.7854" actuatorfrcrange="-10 10" class="motor_finger" />
+                      <geom name="finger_outer_left_00" type="mesh" mesh="finger_outer_left_00" class="visual" material="matte_black" />
+                      <geom name="finger_outer_left_01" type="mesh" mesh="finger_outer_left_01" class="visual" material="matte_black" />
+                      <geom name="finger_outer_left_02" type="mesh" mesh="finger_outer_left_02" class="visual" material="pale_silver" />
+                      <geom name="finger_outer_left_collision_00" type="mesh" mesh="finger_outer_left_collision_00" class="collision" />
+                      <geom name="finger_outer_left_collision_01" type="mesh" mesh="finger_outer_left_collision_01" class="collision" />
+                      <geom name="finger_outer_left_collision_02" type="mesh" mesh="finger_outer_left_collision_02" class="collision" />
+                      <geom name="finger_outer_left_collision_03" type="mesh" mesh="finger_outer_left_collision_03" class="collision" />
+                    </body>
+                  </body>
+                </body>
+              </body>
+            </body>
+          </body>
+        </body>
+      </body>
+    </body>
+    <body name="openarm_right_base_link" pos="0 -0.031 0">
+      <inertial pos="-0.00253124 -0.0258186 -2.70658e-05" quat="2.1457591538e-05 0.706815721259 0.70739772103 -1.46856942085e-06" mass="1.14323" diaginertia="0.00159935 0.00113608 0.000750542" />
+      <geom name="base_link_right_00" type="mesh" mesh="base_link_right_00" class="visual" material="matte_black" quat="0 0 1 0" />
+      <geom name="base_link_right_01" type="mesh" mesh="base_link_right_01" class="visual" material="pale_silver" quat="0 0 1 0" />
+      <geom name="base_link_right_collision_00" type="mesh" mesh="base_link_right_collision_00" class="collision" quat="0 0 1 0" />
+      <body name="openarm_right_link1" pos="0 -0.0625 0">
+        <inertial pos="0.00090035 -0.044466 2.88441e-05" quat="0.999901 0.000371041 -5.04627e-05 0.0140338" mass="1.14167" diaginertia="0.00109459 0.000758935 0.000670659" />
+        <joint name="openarm_right_joint1" pos="0 0 0" axis="0 -1 0" range="-1.3963 3.4907" actuatorfrcrange="-40 40" class="motor_DM8009" />
+        <geom name="link1_right_00" type="mesh" mesh="link1_right_00" class="visual" material="matte_black" />
+        <geom name="link1_right_01" type="mesh" mesh="link1_right_01" class="visual" material="pale_silver" />
+        <geom name="link1_right_02" type="mesh" mesh="link1_right_02" class="visual" material="metal_silver" />
+        <geom name="link1_right_collision_00" type="mesh" mesh="link1_right_collision_00" class="collision" />
+        <body name="openarm_right_link2" pos="0 -0.06 0">
+          <inertial pos="-0.0247185 7.60578e-08 -0.0312643" quat="0.999342 6.47495e-06 -0.0362804 -3.02331e-06" mass="0.277509" diaginertia="0.000153968 0.000113062 8.19211e-05" />
+          <joint name="openarm_right_joint2" pos="0 0 0" axis="-1 0 0" range="-0.17453 3.3161" actuatorfrcrange="-40 40" class="motor_DM8009" />
+          <geom name="link2_right_00" type="mesh" mesh="link2_right_00" class="visual" material="matte_black" />
+          <geom name="link2_right_01" type="mesh" mesh="link2_right_01" class="visual" material="metal_silver" />
+          <geom name="link2_right_02" type="mesh" mesh="link2_right_02" class="visual" material="pale_silver" />
+          <geom name="link2_right_collision_00" type="mesh" mesh="link2_right_collision_00" class="collision" />
+          <body name="openarm_right_link3" pos="0 0 -0.06625">
+            <inertial pos="-0.00300862 -0.000514813 -0.109368" quat="0.998906 -0.00891348 0.0458105 0.00280505" mass="1.07386" diaginertia="0.00129561 0.00114038 0.000553361" />
+            <joint name="openarm_right_joint3" pos="0 0 0" axis="0 0 -1" range="-1.5708 1.5708" actuatorfrcrange="-27 27" class="motor_DM4340" />
+            <geom name="link3_right_00" type="mesh" mesh="link3_right_00" class="visual" material="matte_black" />
+            <geom name="link3_right_01" type="mesh" mesh="link3_right_01" class="visual" material="metal_silver" />
+            <geom name="link3_right_02" type="mesh" mesh="link3_right_02" class="visual" material="pale_silver" />
+            <geom name="link3_right_collision_00" type="mesh" mesh="link3_right_collision_00" class="collision" />
+            <body name="openarm_right_link4" pos="0 0 -0.15375">
+              <inertial pos="-0.00310326 -0.00136539 -0.0574601" quat="0.996952 0.00947325 0.00348083 0.0773554" mass="0.634853" diaginertia="0.000469894 0.000433114 0.000245134" />
+              <joint name="openarm_right_joint4" pos="0 0 0" axis="0 -1 0" range="0 2.4435" actuatorfrcrange="-27 27" class="motor_DM4340" />
+              <geom name="link4_right_00" type="mesh" mesh="link4_right_00" class="visual" material="matte_black" />
+              <geom name="link4_right_01" type="mesh" mesh="link4_right_01" class="visual" material="pale_silver" />
+              <geom name="link4_right_02" type="mesh" mesh="link4_right_02" class="visual" material="metal_silver" />
+              <geom name="link4_right_collision_00" type="mesh" mesh="link4_right_collision_00" class="collision" />
+              <body name="openarm_right_link5" pos="0 0 -0.0955">
+                <inertial pos="-0.000737189 -0.000412407 -0.0470938" quat="0.728019 -0.00297125 -0.0023482 0.685547" mass="0.615659" diaginertia="0.000334799 0.00027946 0.000176657" />
+                <joint name="openarm_right_joint5" pos="0 0 0" axis="0 0 -1" range="-1.5708 1.5708" actuatorfrcrange="-7 7" class="motor_DM4310" />
+                <geom name="link5_right_00" type="mesh" mesh="link5_right_00" class="visual" material="matte_black" />
+                <geom name="link5_right_01" type="mesh" mesh="link5_right_01" class="visual" material="pale_silver" />
+                <geom name="link5_right_02" type="mesh" mesh="link5_right_02" class="visual" material="metal_silver" />
+                <geom name="link5_right_collision_00" type="mesh" mesh="link5_right_collision_00" class="collision" />
+                <geom name="link5_right_collision_01" type="mesh" mesh="link5_right_collision_01" class="collision" />
+                <geom name="link5_right_collision_02" type="mesh" mesh="link5_right_collision_02" class="collision" />
+                <body name="openarm_right_link6" pos="0 0 -0.1205">
+                  <inertial pos="2.27438e-05 0.000686496 5.44e-05" quat="0.999832 0.0183155 0.000397003 0.000757974" mass="0.475203" diaginertia="0.000179276 0.000136249 0.000135339" />
+                  <joint name="openarm_right_joint6" pos="0 0 0" axis="0 1 0" range="-0.7854 0.7854" actuatorfrcrange="-7 7" class="motor_DM4310" />
+                  <geom name="link6_right_00" type="mesh" mesh="link6_right_00" class="visual" material="matte_black" />
+                  <geom name="link6_right_01" type="mesh" mesh="link6_right_01" class="visual" material="metal_silver" />
+                  <geom name="link6_right_02" type="mesh" mesh="link6_right_02" class="visual" material="pale_silver" />
+                  <geom name="link6_right_collision_00" type="mesh" mesh="link6_right_collision_00" class="collision" />
+                  <body name="openarm_right_ee_base_link">
+                    <inertial pos="0.0137902 0.0084073 -0.05938" quat="0.648846 0.760121 0.0169317 0.0304587" mass="0.52832" diaginertia="0.000219417 0.000166122 0.000155742" />
+                    <joint name="openarm_right_joint7" pos="0 0 0" axis="1 0 0" range="-1.5708 1.5708" actuatorfrcrange="-7 7" class="motor_DM3507" />
+                    <geom name="ee_base_link_right_00" pos="0.0205 0 0" quat="1 0 0 0" type="mesh" mesh="ee_base_link_right_00" class="visual" material="matte_black" />
+                    <geom name="ee_base_link_right_01" pos="0.0205 0 0" type="mesh" mesh="ee_base_link_right_01" class="visual" material="metal_silver" />
+                    <geom name="ee_base_link_right_02" pos="0.0205 0 0" type="mesh" mesh="ee_base_link_right_02" class="visual" material="pale_silver" />
+                    <geom name="ee_base_link_right_collision_00" pos="0.0205 0 0" quat="1 0 0 0" type="mesh" mesh="ee_base_link_right_collision_00" class="collision" />
+                    <camera name="camera_wrist_right" pos="0.023 -0.0182 -0.10236" euler="0.366519 0.22689 -1.5708" fovy="66" resolution="960 600"/>
+                    <site name="right_ee_control_point" pos="0.0 0.0 0.0" size="0.01" rgba="1 0 0 1" />
+                    <body name="openarm_right_ee_inner_finger" pos="-0.00143 0.018 -0.068">
+                      <inertial pos="-0.0124991 0.00176593 -0.0241663" quat="0.982638 -0.0922084 -0.15927 0.0235197" mass="0.125979" diaginertia="3.8543e-05 3.6883e-05 1.43942e-05" />
+                      <joint name="openarm_right_finger_joint1" pos="0 0 0" axis="-1 0 0" range="-0.7854 0" actuatorfrcrange="-10 10" class="motor_finger" />
+                      <geom name="finger_inner_right_00" type="mesh" mesh="finger_inner_right_00" class="visual" material="matte_black" />
+                      <geom name="finger_inner_right_01" type="mesh" mesh="finger_inner_right_01" class="visual" material="matte_black" />
+                      <geom name="finger_inner_right_02" type="mesh" mesh="finger_inner_right_02" class="visual" material="pale_silver" />
+                      <geom name="finger_inner_right_collision_00" type="mesh" mesh="finger_inner_right_collision_00" class="collision" />
+                      <geom name="finger_inner_right_collision_01" type="mesh" mesh="finger_inner_right_collision_01" class="collision" />
+                      <geom name="finger_inner_right_collision_02" type="mesh" mesh="finger_inner_right_collision_02" class="collision" />
+                      <geom name="finger_inner_right_collision_03" type="mesh" mesh="finger_inner_right_collision_03" class="collision" />
+                    </body>
+                    <body name="openarm_right_ee_outer_finger" pos="-0.00143 -0.018 -0.068">
+                      <inertial pos="-0.012796 -0.0020183 -0.026792" quat="0.982097 0.0906989 -0.165079 -0.00294117" mass="0.11372" diaginertia="3.70662e-05 3.60159e-05 1.33599e-05" />
+                      <joint name="openarm_right_finger_joint2" pos="0 0 0" axis="1 0 0" range="-0.7854 0" actuatorfrcrange="-10 10" class="motor_finger" />
+                      <geom name="finger_outer_right_00" type="mesh" mesh="finger_outer_right_00" class="visual" material="matte_black" />
+                      <geom name="finger_outer_right_01" type="mesh" mesh="finger_outer_right_01" class="visual" material="matte_black" />
+                      <geom name="finger_outer_right_02" type="mesh" mesh="finger_outer_right_02" class="visual" material="pale_silver" />
+                      <geom name="finger_outer_right_collision_00" type="mesh" mesh="finger_outer_right_collision_00" class="collision" />
+                      <geom name="finger_outer_right_collision_01" type="mesh" mesh="finger_outer_right_collision_01" class="collision" />
+                      <geom name="finger_outer_right_collision_02" type="mesh" mesh="finger_outer_right_collision_02" class="collision" />
+                      <geom name="finger_outer_right_collision_03" type="mesh" mesh="finger_outer_right_collision_03" class="collision" />
+                    </body>
+                  </body>
+                </body>
+              </body>
+            </body>
+          </body>
+        </body>
+      </body>
+    </body>
+  </worldbody>
+  <equality>
+    <joint name="openarm_left_ee_finger_joint_mimic" joint1="openarm_left_finger_joint1" joint2="openarm_left_finger_joint2" polycoef="0 1 0 0 0" solimp="0.95 0.99 0.001" solref="0.005 1" />
+    <joint name="openarm_right_ee_finger_joint_mimic" joint1="openarm_right_finger_joint1" joint2="openarm_right_finger_joint2" polycoef="0 1 0 0 0" solimp="0.95 0.99 0.001" solref="0.005 1" />
+  </equality>
+  <actuator>
+    <position name="left_joint1_ctrl" joint="openarm_left_joint1" class="position_DM8009" kp="230" kv="2.7" ctrllimited="true" ctrlrange="-3.49066 1.39626" />
+    <position name="left_joint2_ctrl" joint="openarm_left_joint2" class="position_DM8009" kp="230" kv="2.7" ctrllimited="true" ctrlrange="-3.31613 0.174533" />
+    <position name="left_joint3_ctrl" joint="openarm_left_joint3" class="position_DM4340" kp="190" kv="2.2" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="left_joint4_ctrl" joint="openarm_left_joint4" class="position_DM4340" kp="190" kv="2.2" ctrllimited="true" ctrlrange="0 2.44346" />
+    <position name="left_joint5_ctrl" joint="openarm_left_joint5" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="left_joint6_ctrl" joint="openarm_left_joint6" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-0.785398 0.785398" />
+    <position name="left_joint7_ctrl" joint="openarm_left_joint7" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="left_finger1_ctrl" joint="openarm_left_finger_joint1" class="position_DM4310" kp="30" kv="0.2" ctrllimited="true" ctrlrange="0 0.7854" />
+    <position name="right_joint1_ctrl" joint="openarm_right_joint1" class="position_DM8009" kp="230" kv="2.7" ctrllimited="true" ctrlrange="-1.39626 3.49066" />
+    <position name="right_joint2_ctrl" joint="openarm_right_joint2" class="position_DM8009" kp="230" kv="2.7" ctrllimited="true" ctrlrange="-0.174533 3.31613" />
+    <position name="right_joint3_ctrl" joint="openarm_right_joint3" class="position_DM4340" kp="190" kv="2.2" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="right_joint4_ctrl" joint="openarm_right_joint4" class="position_DM4340" kp="190" kv="2.2" ctrllimited="true" ctrlrange="0 2.44346" />
+    <position name="right_joint5_ctrl" joint="openarm_right_joint5" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="right_joint6_ctrl" joint="openarm_right_joint6" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-0.785398 0.785398" />
+    <position name="right_joint7_ctrl" joint="openarm_right_joint7" class="position_DM4310" kp="30" kv="1.5" ctrllimited="true" ctrlrange="-1.5708 1.5708" />
+    <position name="right_finger1_ctrl" joint="openarm_right_finger_joint1" class="position_DM4310" kp="30" kv="0.2" ctrllimited="true" ctrlrange="-0.7854 0" />
+  </actuator>
+  <contact>
+
+  </contact>
+</mujoco>
diff --git a/src/unilab/assets/robots/openarm_mujoco_v2/pedestal.xml b/src/unilab/assets/robots/openarm_mujoco_v2/pedestal.xml
new file mode 100644
index 000000000..ff57f0ee5
--- /dev/null
+++ b/src/unilab/assets/robots/openarm_mujoco_v2/pedestal.xml
@@ -0,0 +1,72 @@
+<!--
+Copyright 2026 Enactic, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+<mujoco model="openarm_v20_pedestal">
+  <compiler meshdir="assets" angle="radian"/>
+
+  <default>
+    <default class="visual">
+      <geom contype="0" conaffinity="0" group="2" />
+    </default>
+    <default class="collision">
+      <geom condim="3" conaffinity="1" priority="1" group="3" solref="0.005 1" friction="1 0.01 0.01" />
+    </default>
+  </default>
+
+  <statistic center="1.3 0 0.6" extent="3.5" meansize="0.05"/>
+  <option timestep="0.001" />
+
+  <visual>
+    <headlight diffuse="0.6 0.6 0.6" ambient="0.3 0.3 0.3" specular="0 0 0"/>
+    <rgba haze="0.15 0.25 0.35 1"/>
+    <global azimuth="0" elevation="0"/>
+    <quality shadowsize="8192"/>
+  </visual>
+
+  <asset>
+    <texture type="skybox" builtin="gradient" rgb1="0.3 0.5 0.7" rgb2="0 0 0" width="512" height="3072"/>
+    <texture type="2d" name="groundplane" builtin="checker" mark="edge" rgb1="0.2 0.3 0.4" rgb2="0.1 0.2 0.3"
+      markrgb="0.8 0.8 0.8" width="300" height="300"/>
+    <material name="groundplane" texture="groundplane" texuniform="true" texrepeat="5 5" reflectance="0.2"/>
+    <material name="openarm_body_link0_material" rgba="0.247 0.247 0.247 1.0" reflectance="0.05" shininess="0.5"/>
+
+    <mesh name="body_link0"      content_type="model/stl" file="visual/body/body_link0.stl"           scale="0.001 0.001 0.001" />
+    <mesh name="body_link0_symp" content_type="model/stl" file="collision/body_link0_symp.stl"   scale="0.001 0.001 0.001" />
+
+    <model name="bimanual" file="openarm_bimanual.xml"/>
+  </asset>
+
+  <worldbody>
+    <light pos="0 0 2" dir="0 0 -1" directional="true"/>
+    <geom name="floor" size="0 0 0.05" type="plane" material="groundplane"/>
+
+    <!-- static fixation base -->
+    <geom name="openarm_body_link0_visual"    type="mesh" mesh="body_link0"      class="visual"    material="openarm_body_link0_material" />
+    <geom name="openarm_body_link0_collision" type="mesh" mesh="body_link0_symp" class="collision" />
+
+    <!-- arms attach at the pedestal top (z=0.698) -->
+    <frame pos="0 0 0.698">
+      <attach model="bimanual" prefix=""/>
+    </frame>
+  </worldbody>
+
+  <keyframe>
+    <key name="home"
+      qpos="0.0 0.0 0.0 1.570796 0.0 0.0 0.0 0.0 0.0
+            0.0 0.0 0.0 1.570796 0.0 0.0 0.0 0.0 0.0" />
+  </keyframe>
+
+</mujoco>
diff --git a/src/unilab/base/backend/mujoco/backend.py b/src/unilab/base/backend/mujoco/backend.py
index d2c9e4013..21e4049f5 100644
--- a/src/unilab/base/backend/mujoco/backend.py
+++ b/src/unilab/base/backend/mujoco/backend.py
@@ -282,6 +282,7 @@ def __init__(
         chunk_size: Optional[int] = None,
         adaptive_chunk_size: bool = False,
         bench_nsteps: int = 1,
+        extra_track_body_names: Sequence[str] = (),
     ):
         scene_context = _build_mujoco_scene_context(scene)
         self.scene_model_file = scene_context.model_file
@@ -291,6 +292,7 @@ def __init__(
         self.terrain_surface_sampler = scene_context.terrain_surface_sampler
         self._scene_cleanup_handle = scene_context.cleanup_handle
         self.add_body_sensors = add_body_sensors
+        self._extra_track_body_names = tuple(extra_track_body_names)
         self._base_name = base_name
         self._push_body_name = push_body_name
         self._model_file = scene_context.model_source
@@ -413,12 +415,38 @@ def _load_base_model(self) -> mujoco.MjModel:
         if isinstance(self._model_file, mujoco.MjModel):
             if self.add_body_sensors:
                 raise ValueError("add_body_sensors is not supported for precompiled MuJoCo models")
-            self._tracked_body_ids = []
+            self._tracked_body_ids: list[int] = []
             self._valid_bnames = []
             model = self._model_file
             self._configure_model(model)
             return model
 
+        if self.add_body_sensors:
+            # Compile the tracking-sensor spec directly to an MjModel. Going through
+            # ``MjSpec.to_xml()`` -> ``from_xml_path()`` corrupts ``<attach>``-ed scenes
+            # under MuJoCo >=3.8 (anonymous nested ``<default>`` -> parse error), so the
+            # in-memory compile is the only round-trip-safe path here.
+            from unilab.base.backend.mujoco.xml import compile_model_with_tracking_sensors
+
+            model, valid_bnames = compile_model_with_tracking_sensors(
+                str(self._model_file),
+                baselink_name=self._base_name,
+                extra_track_body_names=self._extra_track_body_names,
+            )
+            self._tracked_body_ids = []
+            self._valid_bnames = valid_bnames
+            # Resolve tracked-body indices against the *compiled* model. Bodies inside
+            # attached sub-models (end-effector / finger links) are invisible to the raw
+            # XML scan, so ``mj_name2id`` over ``valid_bnames`` is the authoritative map
+            # and is identical to enumeration order for attachment-free models.
+            self._body_id_to_tracked_idx = np.full(model.nbody, -1, dtype=int)
+            for idx, bname in enumerate(self._valid_bnames):
+                bid = mujoco.mj_name2id(model, mujoco.mjtObj.mjOBJ_BODY, bname)
+                if bid >= 0:
+                    self._body_id_to_tracked_idx[bid] = idx
+            self._configure_model(model)
+            return model
+
         model_path, tmp_paths, tracked_body_ids, valid_bnames = self._prepare_model_xml()
         try:
             model = mujoco.MjModel.from_xml_path(model_path)
@@ -427,10 +455,6 @@ def _load_base_model(self) -> mujoco.MjModel:
                 os.remove(tmp_path)
 
         self._tracked_body_ids = tracked_body_ids
-        if self.add_body_sensors:
-            self._body_id_to_tracked_idx = np.full(model.nbody, -1, dtype=int)
-            for idx, bid in enumerate(self._tracked_body_ids):
-                self._body_id_to_tracked_idx[bid] = idx
         self._valid_bnames = valid_bnames
         self._configure_model(model)
         return model
@@ -447,6 +471,7 @@ def _prepare_model_xml(self) -> tuple[str, list[str], list[int], list[str]]:
             model_path, tracked_body_ids, valid_bnames = inject_mujoco_tracking_sensors(
                 model_path,
                 baselink_name=self._base_name,
+                extra_track_body_names=self._extra_track_body_names,
             )
             tmp_paths.append(model_path)
         else:
diff --git a/src/unilab/base/backend/mujoco/playback.py b/src/unilab/base/backend/mujoco/playback.py
index 3138ccb9b..5c901bc3b 100644
--- a/src/unilab/base/backend/mujoco/playback.py
+++ b/src/unilab/base/backend/mujoco/playback.py
@@ -62,6 +62,24 @@ def run_mujoco_playback(
     from unilab.visualization import render_many
 
     cam_kw = dict(camera_kwargs or {})
+    play_video_fps_raw = cam_kw.pop("play_video_fps", None)
+    if play_video_fps_raw is None or str(play_video_fps_raw).strip().lower() in (
+        "",
+        "null",
+        "none",
+    ):
+        fb_fps = env_cfg_value(env, "playback_video_fps", None)
+        if fb_fps is not None and str(fb_fps).strip().lower() not in ("", "null", "none"):
+            play_video_fps_raw = fb_fps
+    hide_raw = cam_kw.pop("play_hide_geom_groups", None)
+    hide_geom_groups: list[int] | None = None
+    if hide_raw is not None and len(hide_raw) > 0:
+        hide_geom_groups = [int(x) for x in list(hide_raw)]
+    if not hide_geom_groups:
+        fb = env_cfg_value(env, "playback_hide_geom_groups", None)
+        if fb is not None and len(fb) > 0:
+            hide_geom_groups = [int(x) for x in list(fb)]
+    render_num_processes = int(cam_kw.pop("render_num_processes", 8))
     use_tracking = bool(cam_kw.pop("cam_tracking", False))
     tracking_env_idx = int(cam_kw.pop("cam_tracking_env_idx", 0))
     tracking_extra_envs = int(cam_kw.pop("cam_tracking_extra_envs", 2))
@@ -90,6 +108,7 @@ def run_mujoco_playback(
                 cam_azimuth=cam_kw.get("cam_azimuth", 90),
                 render_spacing=effective_spacing,
                 marker_positions_list=marker_positions_list,
+                hide_geom_groups=hide_geom_groups,
             )
         else:
             frames = render_many.render_states_get_frames(
@@ -97,9 +116,11 @@ def run_mujoco_playback(
                 model_files,
                 width=1280,
                 height=720,
+                num_processes=render_num_processes,
                 camera_id=-1,
                 render_spacing=effective_spacing,
                 marker_positions_list=marker_positions_list,
+                hide_geom_groups=hide_geom_groups,
                 **cam_kw,
             )
 
@@ -111,7 +132,26 @@ def run_mujoco_playback(
         return None
 
     ctrl_dt = float(env_cfg_value(env, "ctrl_dt", 1.0 / 60.0))
-    write_playback_video(str(output_video), frames, fps=int(1.0 / ctrl_dt))
+    physics_fps = max(1, int(round(1.0 / ctrl_dt)))
+    if play_video_fps_raw is not None and str(play_video_fps_raw).strip().lower() not in (
+        "",
+        "null",
+        "none",
+    ):
+        fps = max(1, min(int(float(play_video_fps_raw)), 480))
+    else:
+        fps = physics_fps
+    out = str(output_video)
+    if record_video:
+        slow = fps < physics_fps
+        print(
+            f"[playback] writing {out}\n"
+            f"  video_fps={fps} physics_hz={physics_fps} ctrl_dt={ctrl_dt:g}s"
+            f" ({'slow motion' if slow else 'matches sim rate'})\n"
+            f"  cam_azimuth={cam_kw.get('cam_azimuth')} cam_elevation={cam_kw.get('cam_elevation')} "
+            f"cam_distance={cam_kw.get('cam_distance')} cam_lookat={cam_kw.get('cam_lookat')}"
+        )
+    write_playback_video(out, frames, fps=fps)
     return str(output_video)
 
 
diff --git a/src/unilab/base/backend/mujoco/xml.py b/src/unilab/base/backend/mujoco/xml.py
index ac54e6e5b..005347deb 100644
--- a/src/unilab/base/backend/mujoco/xml.py
+++ b/src/unilab/base/backend/mujoco/xml.py
@@ -518,9 +518,53 @@ def materialize_mujoco_hfield_attached_scene(
     return model, generated.terrain_origins
 
 
+def compile_model_with_tracking_sensors(
+    model_file: str,
+    baselink_name: str | None = None,
+    extra_track_body_names: Sequence[str] = (),
+) -> tuple[Any, list]:
+    """Build tracking sensors and compile straight to an ``MjModel``.
+
+    This mirrors :func:`inject_mujoco_tracking_sensors` but avoids the
+    ``MjSpec.to_xml()`` -> ``MjModel.from_xml_path()`` round-trip. For scenes
+    that use ``<attach>``-ed sub-models, MuJoCo (>=3.8) serialises each attached
+    model's main ``<default>`` as an *anonymous nested* default, which the XML
+    parser then rejects (``empty class name`` / ``repeated default class name``).
+    Compiling the in-memory spec directly sidesteps that broken round-trip.
+
+    ``extra_track_body_names`` lists bodies inside attached sub-models that the
+    raw-XML body scan cannot see (end-effector / finger links).
+
+    Returns:
+        (compiled_model, valid_bnames)
+    """
+    mujoco = _mujoco_module()
+    _, valid_bnames = _get_named_bodies(model_file)
+    # The baselink is the reference frame for ``_b`` sensors; it must itself be a
+    # tracked body for the backend's zero-copy ``_b`` views to line up. When it
+    # lives inside an attached sub-model the raw scan misses it, so append it here
+    # alongside the explicitly requested extra bodies.
+    for name in (*extra_track_body_names, baselink_name):
+        if name and name not in valid_bnames:
+            valid_bnames.append(name)
+
+    dv_path = create_discardvisual_xml(model_file)
+    try:
+        spec = mujoco.MjSpec.from_file(dv_path)
+    finally:
+        os.remove(dv_path)
+
+    _add_w_sensors(spec, valid_bnames)
+    if baselink_name and baselink_name in valid_bnames:
+        _add_b_sensors(spec, valid_bnames, baselink_name)
+
+    return spec.compile(), valid_bnames
+
+
 def inject_mujoco_tracking_sensors(
     model_file: str,
     baselink_name: str | None = None,
+    extra_track_body_names: Sequence[str] = (),
 ) -> tuple[str, list, list]:
     """Inject tracking sensors for the MuJoCo backend.
 
@@ -528,12 +572,23 @@ def inject_mujoco_tracking_sensors(
     ``baselink_name`` is provided, sensors in the baselink-relative frame
     (``_b``) are added as well.
 
+    ``extra_track_body_names`` lists bodies that live inside ``<attach>``-ed
+    sub-models: the raw-XML scan in ``_get_named_bodies`` cannot see them, so
+    they are appended explicitly (they are resolved against the post-attach
+    ``MjSpec`` when the sensors are added). The backend remaps tracked-body
+    indices from the compiled model, so the placeholder ids below are unused.
+
     Returns:
         (tmp_xml_path, tracked_body_ids, valid_bnames)
     """
     mujoco = _mujoco_module()
     tracked_body_ids, valid_bnames = _get_named_bodies(model_file)
 
+    for name in extra_track_body_names:
+        if name and name not in valid_bnames:
+            valid_bnames.append(name)
+            tracked_body_ids.append(len(tracked_body_ids) + 1)
+
     spec = mujoco.MjSpec.from_file(model_file)
     _add_w_sensors(spec, valid_bnames)
     if baselink_name and baselink_name in valid_bnames:
diff --git a/src/unilab/base/np_env.py b/src/unilab/base/np_env.py
index 29ecfc731..fb56322b4 100644
--- a/src/unilab/base/np_env.py
+++ b/src/unilab/base/np_env.py
@@ -133,6 +133,8 @@ def step(self, actions: np.ndarray) -> NpEnvState:
         backend_result = self._backend.step(ctrl, self._cfg.sim_substeps)
         step_core_time = time.perf_counter() - t0
 
+        self.after_physics_substeps(actions)
+
         t0 = time.perf_counter()
         self._state = self.update_state(self._state)
         update_state_time = time.perf_counter() - t0
@@ -176,6 +178,10 @@ def step(self, actions: np.ndarray) -> NpEnvState:
 
         return self._state
 
+    def after_physics_substeps(self, actions: np.ndarray) -> None:
+        """Hook after physics substeps; subclasses may adjust backend state before update_state."""
+        del actions
+
     def _reset_done_envs(self) -> None:
         assert self._state is not None
         done = self._state.terminated | self._state.truncated
diff --git a/src/unilab/envs/manipulation/__init__.py b/src/unilab/envs/manipulation/__init__.py
index 16b529f14..fcaaa516d 100644
--- a/src/unilab/envs/manipulation/__init__.py
+++ b/src/unilab/envs/manipulation/__init__.py
@@ -2,6 +2,7 @@
 
 __unilab_registry_modules__ = (
     "unilab.envs.manipulation.allegro_inhand",
+    "unilab.envs.manipulation.openarm.pick_place_demo",
     "unilab.envs.manipulation.sharpa_inhand",
     "unilab.envs.manipulation.stewart",
 )
diff --git a/src/unilab/envs/manipulation/openarm/__init__.py b/src/unilab/envs/manipulation/openarm/__init__.py
new file mode 100644
index 000000000..25413f913
--- /dev/null
+++ b/src/unilab/envs/manipulation/openarm/__init__.py
@@ -0,0 +1 @@
+"""OpenArm manipulation envs (MJCF-backed)."""
diff --git a/src/unilab/envs/manipulation/openarm/pick_place_demo.py b/src/unilab/envs/manipulation/openarm/pick_place_demo.py
new file mode 100644
index 000000000..17c3c7ee1
--- /dev/null
+++ b/src/unilab/envs/manipulation/openarm/pick_place_demo.py
@@ -0,0 +1,847 @@
+"""OpenArm bimanual pick / place bring-up on vendored ``demo.xml`` (cell + cube + frame)."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+import gymnasium as gym
+import numpy as np
+
+from unilab.assets import ASSETS_ROOT_PATH
+from unilab.base import registry
+from unilab.base.backend import create_backend
+from unilab.base.base import EnvCfg
+from unilab.base.np_env import NpEnv, NpEnvState
+from unilab.base.scene import SceneCfg
+from unilab.dr.provider import DomainRandomizationProvider
+from unilab.dr.types import DomainRandomizationCapabilities, ResetPlan
+from unilab.dtype_config import get_global_dtype
+from unilab.envs.common.rotation import np_quat_apply_batched
+
+# Position actuators in the vendored model, mapped to their qpos addresses. The lifter prismatic
+# joint sits at index 9 in the full actuator vector and is dropped from the policy action space.
+_ACTUATOR_QPOS_INDICES: tuple[int, ...] = (
+    0,
+    1,
+    2,
+    3,
+    4,
+    5,
+    6,
+    7,
+    8,
+    10,
+    11,
+    12,
+    13,
+    14,
+    15,
+    16,
+    17,
+)
+_NU_FULL = len(_ACTUATOR_QPOS_INDICES)
+_LIFTER_ACTUATOR_NAME = "lifter_ctrl"
+_RIGHT_FREEZE_JOINT_NAMES: tuple[str, ...] = (
+    "openarm_right_joint1",
+    "openarm_right_joint2",
+    "openarm_right_joint3",
+    "openarm_right_joint4",
+    "openarm_right_joint5",
+    "openarm_right_joint6",
+    "openarm_right_joint7",
+    "openarm_right_finger_joint1",
+    "openarm_right_finger_joint2",
+)
+
+
+def _ctrl_from_full_qpos(qpos: np.ndarray) -> np.ndarray:
+    """Extract position-actuator commands from a full MuJoCo qpos vector."""
+    idx = np.asarray(_ACTUATOR_QPOS_INDICES, dtype=np.int64)
+    return np.asarray(qpos[idx], dtype=np.float64)
+
+
+@dataclass
+class OpenArmDemoPickRewardConfig:
+    """Scalar reward weights (Hydra ``reward.scales`` maps onto these names)."""
+
+    scales: dict[str, float] = field(
+        default_factory=lambda: {
+            "reach": 1.0,
+            "place": 0.8,
+            "lift": 0.35,
+            "grasp": 0.22,
+            "settle": 0.0,
+            "success": 25.0,
+            "hold_success": 0.0,
+            "action": -0.01,
+            "drop": -1.0,
+            "lift_bonus": 0.0,
+            "goal_track_coarse": 0.0,
+            "goal_track_fine": 0.0,
+            # Staged-grasp shaping (off by default; enabled via the contgrip config).
+            "approach": 0.0,
+            "premature_close": 0.0,
+            "action_rate": 0.0,
+            "firm_grasp": 0.0,
+        }
+    )
+
+    fall_z: float = 0.92
+    success_xy: float = 0.028
+    lift_z: float = 1.04
+
+    table_z: float = 1.008
+    lift_shaping_span: float = 0.12
+
+    grasp_proximity_decay: float = 6.0
+
+    # ``place`` is gated by finger closure × EE-cube proximity.
+    place_use_grasp_gate: bool = True
+
+    # Legacy flag kept for backward compatibility; superseded by ``lift_gate_mode``.
+    lift_use_grasp_gate: bool = False
+
+    # ``grasp`` (closure×proximity) / ``proximity`` (EE-cube only) / ``none``.
+    lift_gate_mode: str | None = None
+
+    settle_xy_decay: float = 12.0
+    settle_arm_vel_coeff: float = 0.03
+    settle_use_lift_gate: bool = True
+
+    terminate_on_success: bool = True
+
+    reach_use_tcp: bool = False
+
+    # Local offset (m) applied at the fingertip TCP, expressed in the inner-finger frame.
+    reach_tcp_offset: tuple[float, float, float] = (0.0, 0.0, 0.0)
+
+    goal_success_mode: str = "xy_lift"
+
+    success_dist: float = 0.05
+
+    lift_margin: float = 0.05
+
+    goal_track_coarse_std: float = 0.1
+    goal_track_fine_std: float = 0.03
+
+    # --- Staged-grasp shaping (used by ``approach`` / ``premature_close``) ---
+    # Pre-grasp clearance above the cube that the ``approach`` term rewards
+    # hovering at (with the gripper still open).
+    pregrasp_h: float = 0.10
+    approach_xy_decay: float = 8.0
+    approach_z_decay: float = 8.0
+    # Closure far from the cube (in xy) is penalized to discourage grasping at air.
+    premature_close_decay: float = 8.0
+
+
+@registry.envcfg("OpenArmDemoPick")
+@dataclass
+class OpenArmDemoPickCfg(EnvCfg):
+    scene: SceneCfg = field(
+        default_factory=lambda: SceneCfg(
+            model_file=str(ASSETS_ROOT_PATH / "robots" / "openarm_mujoco_v2" / "demo.xml")
+        )
+    )
+
+    sim_dt: float = 0.002
+    ctrl_dt: float = 0.02
+    max_episode_seconds: float = 40.0
+    render_spacing: float = 2.0
+
+    base_name: str = "openarm_lifter_link"
+    action_scale: float = 0.04
+    reward_config: OpenArmDemoPickRewardConfig | None = None
+
+    goal_pos: tuple[float, float, float] = (0.52, 0.0, 1.03)
+    cube_xy_range: tuple[float, float, float, float] = (0.4, 0.5, -0.06, 0.06)
+    cube_spawn_z: float = 1.05
+    fix_lifter: bool = True
+    left_arm_only: bool = False
+    rigid_freeze_right_arm: bool = False
+
+    binary_gripper: bool = False
+
+    playback_hide_geom_groups: tuple[int, ...] | None = None
+    playback_video_fps: float | None = None
+
+    def validate(self) -> None:
+        super().validate()
+        if self.reward_config is None:
+            raise ValueError("reward_config must be set (typically via Hydra `reward` block)")
+        if self.left_arm_only and not self.fix_lifter:
+            raise ValueError("left_arm_only=True requires fix_lifter=True")
+        if self.rigid_freeze_right_arm and not self.left_arm_only:
+            raise ValueError("rigid_freeze_right_arm=True requires left_arm_only=True")
+        mode = self.reward_config.goal_success_mode
+        if mode not in ("xy_lift", "lift3d"):
+            raise ValueError(
+                f"reward_config.goal_success_mode must be 'xy_lift' or 'lift3d', got {mode!r}"
+            )
+
+
+class OpenArmDemoPickDRProvider(DomainRandomizationProvider):
+    """Keyframe robot reset + randomized cube pose on the table."""
+
+    def validate(self, env: Any, capabilities: DomainRandomizationCapabilities) -> None:
+        pass
+
+    def build_reset_plan(self, env: "OpenArmDemoPickEnv", env_ids: np.ndarray) -> ResetPlan:
+        cfg = env._cfg
+        n = int(env_ids.shape[0])
+        home = np.asarray(env._backend.get_keyframe_qpos("home"), dtype=np.float64)
+        qpos = np.broadcast_to(home, (n, home.shape[0])).copy()
+        (low_x, high_x, low_y, high_y) = cfg.cube_xy_range
+        qpos[:, 19] = np.random.uniform(low_x, high_x, size=(n,))
+        qpos[:, 20] = np.random.uniform(low_y, high_y, size=(n,))
+        qpos[:, 21] = float(cfg.cube_spawn_z)
+        qpos[:, 22:26] = np.tile(np.array([1, 0, 0, 0], dtype=np.float64), (n, 1))
+        qvel = np.zeros((n, env.nv), dtype=np.float64)
+        home_ctrl = _ctrl_from_full_qpos(home)
+        home_ctrl_b = np.broadcast_to(home_ctrl, (n, _NU_FULL)).astype(
+            get_global_dtype(), copy=False
+        )
+        info_updates = {
+            "last_actions": np.zeros((n, env.num_policy_actions), dtype=get_global_dtype()),
+            "prev_actions": np.zeros((n, env.num_policy_actions), dtype=get_global_dtype()),
+            "prev_ctrl": home_ctrl_b.copy(),
+            "goal_pos": np.broadcast_to(
+                np.asarray(cfg.goal_pos, dtype=get_global_dtype()), (n, 3)
+            ).copy(),
+        }
+        return ResetPlan(
+            env_ids=env_ids, qpos=qpos, qvel=qvel, info_updates=info_updates, randomization=None
+        )
+
+    def build_reset_observation(
+        self,
+        env: "OpenArmDemoPickEnv",
+        env_ids: np.ndarray,
+        info_updates: dict[str, Any],
+    ) -> dict[str, np.ndarray]:
+        rows = np.asarray(env_ids, dtype=np.intp)
+        obs = env._assemble_obs_rows(rows, info_updates["goal_pos"], info_updates["last_actions"])
+        return {"obs": obs}
+
+
+@registry.env("OpenArmDemoPick", sim_backend="mujoco")
+class OpenArmDemoPickEnv(NpEnv):
+    """Pick / place on the orange cube: EE-centric reach shaping (left or right arm per cfg)."""
+
+    _cfg: OpenArmDemoPickCfg
+
+    def __init__(self, cfg: OpenArmDemoPickCfg, num_envs: int, backend_type: str) -> None:
+        if cfg.reward_config is None:
+            raise ValueError("reward_config must be provided via Hydra configuration")
+        cfg.validate()
+
+        arm = "left" if cfg.left_arm_only else "right"
+        ee_body = f"openarm_{arm}_ee_base_link"
+        extra_track_body_names = (
+            ee_body,
+            f"openarm_{arm}_ee_inner_finger",
+            f"openarm_{arm}_ee_outer_finger",
+        )
+
+        backend = create_backend(
+            backend_type,
+            cfg.scene,
+            num_envs,
+            cfg.sim_dt,
+            base_name=cfg.base_name,
+            add_body_sensors=True,
+            extra_track_body_names=extra_track_body_names,
+        )
+        super().__init__(cfg, backend, num_envs)
+
+        self._np_dtype = get_global_dtype()
+        self._reward_cfg = cfg.reward_config
+
+        self._reward_fns = {
+            "reach": self._reward_reach,
+            "place": self._reward_place,
+            "lift": self._reward_lift,
+            "grasp": self._reward_grasp,
+            "settle": self._reward_settle,
+            "success": self._reward_success,
+            "hold_success": self._reward_hold_success,
+            "action": self._reward_action,
+            "drop": self._reward_drop,
+            "lift_bonus": self._reward_lift_bonus,
+            "goal_track_coarse": self._reward_goal_track_coarse,
+            "goal_track_fine": self._reward_goal_track_fine,
+            "approach": self._reward_approach,
+            "premature_close": self._reward_premature_close,
+            "action_rate": self._reward_action_rate,
+            "firm_grasp": self._reward_firm_grasp,
+        }
+
+        act_range = np.asarray(self._backend.get_actuator_ctrl_range(), dtype=self._np_dtype)
+        if int(act_range.shape[0]) != _NU_FULL:
+            raise ValueError(f"Expected {_NU_FULL} actuators, got {act_range.shape[0]}")
+        self._ctrl_lo = act_range[:, 0]
+        self._ctrl_hi = act_range[:, 1]
+        self._ctrl_mid = (self._ctrl_lo + self._ctrl_hi) * 0.5
+        self._ctrl_span = (self._ctrl_hi - self._ctrl_lo) + 1e-08
+
+        self._fix_lifter = bool(cfg.fix_lifter)
+        self._left_arm_only = bool(cfg.left_arm_only)
+
+        if self._fix_lifter:
+            import mujoco
+
+            m = self._backend.model
+            li = int(mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_ACTUATOR, _LIFTER_ACTUATOR_NAME))
+            if li < 0:
+                raise ValueError(
+                    f"fix_lifter=True requires actuator {_LIFTER_ACTUATOR_NAME!r} in the scene."
+                )
+            self._lifter_actuator_idx = li
+            home = np.asarray(self._backend.get_keyframe_qpos("home"), dtype=np.float64)
+            home_ctrl = _ctrl_from_full_qpos(home)
+            lifter_u = home_ctrl[self._lifter_actuator_idx]
+            self._lifter_fixed_ctrl = self._np_dtype.type(lifter_u)
+
+            if self._left_arm_only:
+                self._policy_active_actuator_idx = np.arange(1, 9, dtype=np.int64)
+                self._right_actuator_idx = np.arange(9, 17, dtype=np.int64)
+                self._policy_qpos_ix = np.asarray(_ACTUATOR_QPOS_INDICES[1:9], dtype=np.int64)
+                self._num_policy_action = 8
+                self._right_fixed_ctrl = np.asarray(
+                    home_ctrl[self._right_actuator_idx], dtype=self._np_dtype
+                )
+                self._ctrl_mid_policy = self._ctrl_mid[self._policy_active_actuator_idx]
+                self._ctrl_span_policy = self._ctrl_span[self._policy_active_actuator_idx]
+            else:
+                self._right_actuator_idx = np.empty(0, dtype=np.int64)
+                self._right_fixed_ctrl = np.empty(0, dtype=self._np_dtype)
+                self._policy_active_actuator_idx = np.array(
+                    [i for i in range(_NU_FULL) if i != li], dtype=np.int64
+                )
+                self._arm_actuator_idx = self._policy_active_actuator_idx.copy()
+                if int(self._arm_actuator_idx.size) != _NU_FULL - 1:
+                    raise RuntimeError("internal: expected one lifter actuator to drop from policy")
+                self._policy_qpos_ix = np.asarray(_ACTUATOR_QPOS_INDICES[1:], dtype=np.int64)
+                self._num_policy_action = _NU_FULL - 1
+                self._ctrl_mid_policy = self._ctrl_mid[self._arm_actuator_idx]
+                self._ctrl_span_policy = self._ctrl_span[self._arm_actuator_idx]
+        else:
+            self._lifter_actuator_idx = -1
+            self._arm_actuator_idx = np.arange(_NU_FULL, dtype=np.int64)
+            self._policy_active_actuator_idx = self._arm_actuator_idx.copy()
+            self._right_actuator_idx = np.empty(0, dtype=np.int64)
+            self._right_fixed_ctrl = np.empty(0, dtype=self._np_dtype)
+            self._policy_qpos_ix = np.asarray(_ACTUATOR_QPOS_INDICES, dtype=np.int64)
+            self._num_policy_action = _NU_FULL
+            self._lifter_fixed_ctrl = self._np_dtype.type(0.0)
+            self._ctrl_mid_policy = self._ctrl_mid
+            self._ctrl_span_policy = self._ctrl_span
+
+        self._grasp_finger_actuator_idx = None
+        if self._fix_lifter and self._left_arm_only:
+            self._grasp_finger_actuator_idx = int(self._policy_active_actuator_idx[-1])
+
+        self._binary_gripper = bool(cfg.binary_gripper)
+        if self._binary_gripper and self._grasp_finger_actuator_idx is None:
+            raise ValueError(
+                "binary_gripper=True requires a resolvable gripper actuator "
+                "(fix_lifter=True and left_arm_only=True)."
+            )
+
+        self._policy_obs_dim = self._num_policy_action * 2 + 6
+
+        self._cube_body_ids = self._backend.get_body_ids(["orange_cube"])
+        self._ee_body_ids = self._backend.get_body_ids([ee_body])
+
+        self._use_tcp = bool(self._reward_cfg.reach_use_tcp)
+        self._tcp_body_ids = None
+
+        self._tcp_offset_local = np.asarray(self._reward_cfg.reach_tcp_offset, dtype=self._np_dtype)
+        self._tcp_has_offset = bool(np.any(self._tcp_offset_local != 0.0))
+
+        if self._use_tcp:
+            arm = "left" if self._left_arm_only else "right"
+            finger_bodies = [
+                f"openarm_{arm}_ee_inner_finger",
+                f"openarm_{arm}_ee_outer_finger",
+            ]
+            try:
+                self._tcp_body_ids = self._backend.get_body_ids(finger_bodies)
+            except (ValueError, KeyError):
+                self._tcp_body_ids = None
+            if self._tcp_body_ids is None:
+                raise ValueError(
+                    f"reach_use_tcp=True requires finger bodies {finger_bodies!r} in the scene."
+                )
+
+        self._settle_dof_vel_ix = None
+        if self._backend.backend_type == "mujoco":
+            arm = "left" if self._left_arm_only else "right"
+            jn = tuple(f"openarm_{arm}_joint{i}" for i in range(1, 8)) + (
+                f"openarm_{arm}_finger_joint1",
+            )
+            try:
+                self._settle_dof_vel_ix = np.asarray(
+                    self._backend.get_joint_dof_vel_indices(jn), dtype=np.int64
+                )
+            except ValueError:
+                self._settle_dof_vel_ix = None
+
+        self._action_space = gym.spaces.Box(-1.0, 1.0, (self._num_policy_action,), dtype=np.float32)
+        self.nq = int(self._backend.model.nq)
+        self.nv = int(self._backend.model.nv)
+
+        self._init_domain_randomization(OpenArmDemoPickDRProvider())
+
+        self._rigid_freeze_right_arm = bool(cfg.rigid_freeze_right_arm)
+        self._right_freeze_qadr = None
+        self._right_freeze_dofadr = None
+        self._home_right_qpos_freeze = None
+        if (
+            self._left_arm_only
+            and self._rigid_freeze_right_arm
+            and self._backend.backend_type == "mujoco"
+        ):
+            import mujoco
+
+            mm = self._backend.model
+            qadr: list[int] = []
+            dofadr: list[int] = []
+            for joint_name in _RIGHT_FREEZE_JOINT_NAMES:
+                jid = int(mujoco.mj_name2id(mm, mujoco.mjtObj.mjOBJ_JOINT, joint_name))
+                if jid < 0:
+                    raise ValueError(f"joint {joint_name!r} not found for rigid_freeze_right_arm")
+                qadr.append(int(mm.jnt_qposadr[jid]))
+                dofadr.append(int(mm.jnt_dofadr[jid]))
+            self._right_freeze_qadr = np.asarray(qadr, dtype=np.int64)
+            self._right_freeze_dofadr = np.asarray(dofadr, dtype=np.int64)
+            home_q = np.asarray(self._backend.get_keyframe_qpos("home"), dtype=np.float64)
+            self._home_right_qpos_freeze = home_q[self._right_freeze_qadr].astype(
+                self._np_dtype, copy=False
+            )
+
+    def after_physics_substeps(self, actions: np.ndarray) -> None:
+        del actions
+        if not (
+            self._left_arm_only
+            and self._rigid_freeze_right_arm
+            and self._right_freeze_qadr is not None
+            and self._home_right_qpos_freeze is not None
+            and self._right_freeze_dofadr is not None
+        ):
+            return
+        fn = getattr(self._backend, "hard_set_joint_subset_and_forward", None)
+        if fn is None:
+            return
+        fn(
+            qpos_adrs=self._right_freeze_qadr,
+            qpos_values=self._home_right_qpos_freeze,
+            dof_adrs=self._right_freeze_dofadr,
+        )
+
+    @property
+    def num_policy_actions(self) -> int:
+        return int(self._num_policy_action)
+
+    @property
+    def action_space(self) -> gym.spaces.Box:
+        return self._action_space
+
+    @property
+    def obs_groups_spec(self) -> dict[str, int]:
+        return {"obs": int(self._policy_obs_dim)}
+
+    def apply_action(self, actions: np.ndarray, state: NpEnvState) -> np.ndarray:
+        clipped = np.clip(np.asarray(actions, dtype=self._np_dtype), -1.0, 1.0)
+        prev_actions = state.info.get("last_actions")
+        if prev_actions is not None:
+            state.info["prev_actions"] = np.asarray(prev_actions, dtype=self._np_dtype)
+        state.info["last_actions"] = clipped
+        prev = state.info["prev_ctrl"]
+        if self._fix_lifter:
+            nxt = np.asarray(prev, dtype=self._np_dtype, copy=True)
+            li = int(self._lifter_actuator_idx)
+            nxt[:, li] = self._lifter_fixed_ctrl
+            if self._left_arm_only:
+                ri = self._right_actuator_idx
+                nxt[:, ri] = self._right_fixed_ctrl
+                active = self._policy_active_actuator_idx
+                nxt[:, active] = prev[:, active] + self._cfg.action_scale * clipped
+                nxt[:, active] = np.clip(
+                    nxt[:, active], self._ctrl_lo[active], self._ctrl_hi[active]
+                )
+                if self._binary_gripper and self._grasp_finger_actuator_idx is not None:
+                    gi = int(self._grasp_finger_actuator_idx)
+                    close = clipped[:, -1] > 0.0
+                    nxt[:, gi] = np.where(close, self._ctrl_hi[gi], self._ctrl_lo[gi]).astype(
+                        self._np_dtype
+                    )
+            else:
+                arm_ix = self._arm_actuator_idx
+                nxt[:, arm_ix] = prev[:, arm_ix] + self._cfg.action_scale * clipped
+                nxt[:, arm_ix] = np.clip(
+                    nxt[:, arm_ix], self._ctrl_lo[arm_ix], self._ctrl_hi[arm_ix]
+                )
+        else:
+            nxt = prev + self._cfg.action_scale * clipped
+            nxt = np.clip(nxt, self._ctrl_lo, self._ctrl_hi)
+        state.info["prev_ctrl"] = np.asarray(nxt, dtype=self._np_dtype)
+        return state.info["prev_ctrl"]
+
+    def _dof_cmd_positions_policy(self) -> np.ndarray:
+        full = np.asarray(self._backend.get_dof_pos(), dtype=self._np_dtype)
+        return full[:, self._policy_qpos_ix]
+
+    def _grasp_point_w(self, rows: np.ndarray | slice | None = None) -> np.ndarray:
+        """End-effector reference point used by reach / grasp / obs.
+
+        Returns the fingertip TCP (midpoint of the two finger bodies) when ``reach_use_tcp`` is
+        set, otherwise the wrist ``ee_base_link`` pose. Shape ``(R, 3)``.
+        """
+        sel = slice(None) if rows is None else rows
+        if self._use_tcp and self._tcp_body_ids is not None:
+            fp = np.asarray(
+                self._backend.get_body_pos_w(self._tcp_body_ids)[sel], dtype=self._np_dtype
+            )
+            mid = np.asarray(fp.mean(axis=1), dtype=self._np_dtype)
+            if self._tcp_has_offset:
+                inner_quat = np.asarray(
+                    self._backend.get_body_quat_w(self._tcp_body_ids)[sel, 0, :],
+                    dtype=self._np_dtype,
+                )
+                mid = mid + np_quat_apply_batched(inner_quat, self._tcp_offset_local)
+            return mid
+        return np.asarray(
+            self._backend.get_body_pos_w(self._ee_body_ids)[sel, 0, :], dtype=self._np_dtype
+        )
+
+    def _assemble_obs_rows(
+        self, env_rows: np.ndarray, goal: np.ndarray, last_actions: np.ndarray
+    ) -> np.ndarray:
+        dof_cmd = self._dof_cmd_positions_policy()[env_rows]
+        dof_norm = (dof_cmd - self._ctrl_mid_policy) / (0.5 * self._ctrl_span_policy)
+        ee = self._grasp_point_w(env_rows)
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[env_rows, 0, :],
+            dtype=self._np_dtype,
+        )
+        return np.concatenate(
+            [dof_norm, ee - cube, goal - cube, last_actions], axis=1, dtype=self._np_dtype
+        )
+
+    def _compute_obs(self, info: dict[str, Any]) -> dict[str, np.ndarray]:
+        rows = np.arange(self._num_envs, dtype=np.intp)
+        obs = self._assemble_obs_rows(rows, info["goal_pos"], info["last_actions"])
+        return {"obs": obs}
+
+    def update_state(self, state: NpEnvState) -> NpEnvState:
+        info = dict(state.info)
+        obs = self._compute_obs(info)
+        cube_pos = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        cube_z = cube_pos[:, 2]
+        fallen = cube_z < self._reward_cfg.fall_z
+        if self._reward_cfg.goal_success_mode == "lift3d":
+            goal = np.asarray(info["goal_pos"], dtype=self._np_dtype)
+            dist_3d = np.linalg.norm(cube_pos - goal, axis=-1)
+            lifted = cube_z > (
+                self._np_dtype.type(self._reward_cfg.table_z)
+                + self._np_dtype.type(self._reward_cfg.lift_margin)
+            )
+            success = (dist_3d < self._reward_cfg.success_dist) & lifted
+        else:
+            cube_xy = cube_pos[:, :2]
+            goal_xy = info["goal_pos"][:, :2]
+            dist_xy = np.linalg.norm(cube_xy - goal_xy, axis=-1)
+            lifted = cube_z > self._reward_cfg.lift_z
+            success = (dist_xy < self._reward_cfg.success_xy) & lifted
+        if self._reward_cfg.terminate_on_success:
+            terminated = fallen | success
+        else:
+            terminated = fallen.copy()
+        reward = self._compute_reward(info, fallen, success)
+        info["pick_success"] = success.astype(bool)
+        info["pick_fallen"] = fallen.astype(bool)
+        return state.replace(
+            obs=obs,
+            reward=reward,
+            terminated=terminated.astype(bool),
+            info=info,
+        )
+
+    def _compute_reward(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        dtype = self._np_dtype
+        out = np.zeros((self._num_envs,), dtype=dtype)
+        for name, scale in self._reward_cfg.scales.items():
+            if scale == 0.0 or name not in self._reward_fns:
+                continue
+            out += scale * self._reward_fns[name](info, fallen, success)
+        return out * self._cfg.ctrl_dt
+
+    def _reward_reach(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        ee = self._grasp_point_w()
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        dist = np.linalg.norm(ee - cube, axis=-1)
+        return np.exp(-5.0 * dist).astype(self._np_dtype)
+
+    def _reward_place(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        goal = info["goal_pos"]
+        dist = np.linalg.norm(cube - goal, axis=-1)
+        place = np.exp(-8.0 * dist).astype(self._np_dtype)
+        if self._reward_cfg.place_use_grasp_gate:
+            place = place * self._grasp_gate(info)
+        return place
+
+    def _finger_closure(self, info: dict[str, Any]) -> np.ndarray:
+        """[0,1] gripper closure derived from the commanded finger ctrl (0=open, 1=closed)."""
+        n = self._num_envs
+        if self._grasp_finger_actuator_idx is None:
+            return np.zeros((n,), dtype=self._np_dtype)
+        ji = int(self._grasp_finger_actuator_idx)
+        prev = np.asarray(info["prev_ctrl"], dtype=self._np_dtype)
+        f = prev[:, ji]
+        lo = self._np_dtype.type(self._ctrl_lo[ji])
+        hi = self._np_dtype.type(self._ctrl_hi[ji])
+        span = (hi - lo) + self._np_dtype.type(1e-08)
+        return np.clip((f - lo) / span, 0.0, 1.0).astype(self._np_dtype)
+
+    def _grasp_gate(self, info: dict[str, Any]) -> np.ndarray:
+        """[0,1] gate: finger closure × proximity of EE to cube (same as unscaled ``grasp`` term)."""
+        n = self._num_envs
+        if self._grasp_finger_actuator_idx is None:
+            return np.ones((n,), dtype=self._np_dtype)
+        closure = self._finger_closure(info)
+        ee = self._grasp_point_w()
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        dist = np.linalg.norm(ee - cube, axis=-1)
+        k = self._np_dtype.type(self._reward_cfg.grasp_proximity_decay)
+        prox = np.exp(-k * dist).astype(self._np_dtype)
+        return (closure * prox).astype(self._np_dtype)
+
+    def _reward_action(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        a = info["last_actions"]
+        return -np.sum(np.square(a), axis=-1).astype(self._np_dtype)
+
+    def _reward_approach(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """[0,1] reward for hovering above the cube with the gripper still open.
+
+        Peaks when the TCP is aligned in xy with the cube and at ``pregrasp_h``
+        above it, scaled by how open the gripper is (``1 - closure``). Encourages
+        the deliberate "go above + keep open" phase before descending to grasp.
+        """
+        del fallen, success
+        ee = self._grasp_point_w()
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        xy = np.linalg.norm(ee[:, :2] - cube[:, :2], axis=-1)
+        pregrasp_z = cube[:, 2] + self._np_dtype.type(self._reward_cfg.pregrasp_h)
+        dz = np.abs(ee[:, 2] - pregrasp_z)
+        kx = self._np_dtype.type(self._reward_cfg.approach_xy_decay)
+        kz = self._np_dtype.type(self._reward_cfg.approach_z_decay)
+        openness = (1.0 - self._finger_closure(info)).astype(self._np_dtype)
+        return (np.exp(-kx * xy) * np.exp(-kz * dz) * openness).astype(self._np_dtype)
+
+    def _reward_premature_close(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """Positive penalty magnitude for closing the gripper while far (in xy) from the cube.
+
+        Returns ``closure × (1 - exp(-k·xy))`` in [0,1]; pair with a negative scale.
+        Discourages grabbing at air / closing en route instead of over the cube.
+        """
+        del fallen, success
+        ee = self._grasp_point_w()
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        xy = np.linalg.norm(ee[:, :2] - cube[:, :2], axis=-1)
+        k = self._np_dtype.type(self._reward_cfg.premature_close_decay)
+        far = (1.0 - np.exp(-k * xy)).astype(self._np_dtype)
+        closure = self._finger_closure(info)
+        return (closure * far).astype(self._np_dtype)
+
+    def _reward_firm_grasp(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """[0,1] reward for a *firm* grasp: high finger closure while the cube is
+        lifted and the TCP is on it.
+
+        ``closure × lift_gate × proximity_gate``. The lift gate means this only
+        pays once the cube is actually off the table, so it rewards "hold the
+        cube tightly while carrying it" rather than clamping the jaws at rest --
+        it cannot create a low/no-lift "clamp and sit" optimum. Use to push the
+        policy away from the loose tip-cradle grasp toward genuine pinch force.
+        """
+        del fallen, success
+        closure = self._finger_closure(info)
+        return (closure * self._lift_gate_binary() * self._lift_proximity_gate()).astype(
+            self._np_dtype
+        )
+
+    def _reward_action_rate(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """Positive penalty magnitude = squared change between consecutive actions.
+
+        Returns ``sum((a_t - a_{t-1})^2)``; pair with a negative scale to smooth motion.
+        """
+        del fallen, success
+        a = np.asarray(info["last_actions"], dtype=self._np_dtype)
+        prev = info.get("prev_actions")
+        if prev is None:
+            return np.zeros((self._num_envs,), dtype=self._np_dtype)
+        prev = np.asarray(prev, dtype=self._np_dtype)
+        return np.sum(np.square(a - prev), axis=-1).astype(self._np_dtype)
+
+    def _reward_drop(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del info, success
+        return fallen.astype(self._np_dtype)
+
+    def _reward_lift(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        cube_z = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, 2], dtype=self._np_dtype
+        )
+        span = max(float(self._reward_cfg.lift_shaping_span), 1e-06)
+        h = np.clip(cube_z - self._np_dtype.type(self._reward_cfg.table_z), 0.0, span)
+        progress = (h / span).astype(self._np_dtype)
+        mode = self._reward_cfg.lift_gate_mode
+        if mode is None:
+            mode = "grasp" if self._reward_cfg.lift_use_grasp_gate else "none"
+        if mode == "grasp":
+            progress = (progress * self._grasp_gate(info)).astype(self._np_dtype)
+            return progress
+        if mode == "proximity":
+            progress = (progress * self._lift_proximity_gate()).astype(self._np_dtype)
+            return progress
+        if mode != "none":
+            raise ValueError(
+                f"lift_gate_mode must be one of 'grasp'/'proximity'/'none', got {mode!r}"
+            )
+        return progress
+
+    def _lift_proximity_gate(self) -> np.ndarray:
+        """[0,1] gate = exp(-grasp_proximity_decay · ||tcp - cube||); robust to closure wobble."""
+        ee = self._grasp_point_w()
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        dist = np.linalg.norm(ee - cube, axis=-1)
+        k = self._np_dtype.type(self._reward_cfg.grasp_proximity_decay)
+        return np.exp(-k * dist).astype(self._np_dtype)
+
+    def _reward_grasp(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        return self._grasp_gate(info)
+
+    def _reward_settle(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """Encourage low arm joint speed when the cube is near the goal (optional lift gate)."""
+        del fallen, success
+        n = self._num_envs
+        if self._settle_dof_vel_ix is None:
+            return np.zeros((n,), dtype=self._np_dtype)
+        dof_vel = np.asarray(self._backend.get_dof_vel(), dtype=self._np_dtype)
+        v = dof_vel[:, self._settle_dof_vel_ix]
+        vel_pen = np.sum(v * v, axis=-1)
+        c = self._np_dtype.type(self._reward_cfg.settle_arm_vel_coeff)
+        exp_still = np.exp(-c * vel_pen).astype(self._np_dtype)
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        goal = np.asarray(info["goal_pos"], dtype=self._np_dtype)
+        dist_xy = np.linalg.norm(cube[:, :2] - goal[:, :2], axis=-1)
+        kxy = self._np_dtype.type(self._reward_cfg.settle_xy_decay)
+        gate_xy = np.exp(-kxy * dist_xy).astype(self._np_dtype)
+        if self._reward_cfg.settle_use_lift_gate:
+            span = max(float(self._reward_cfg.lift_shaping_span), 1e-06)
+            h = np.clip(
+                cube[:, 2] - self._np_dtype.type(self._reward_cfg.table_z), 0.0, span
+            ).astype(self._np_dtype)
+            lift_gate = (h / self._np_dtype.type(span)).astype(self._np_dtype)
+            gate = (gate_xy * lift_gate).astype(self._np_dtype)
+        else:
+            gate = gate_xy
+        return (gate * exp_still).astype(self._np_dtype)
+
+    def _reward_success(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del info, fallen
+        return success.astype(self._np_dtype)
+
+    def _reward_hold_success(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """Per-step bonus when ``pick_success`` is true (eval-aligned hold-at-goal)."""
+        del info, fallen
+        return success.astype(self._np_dtype)
+
+    def _lift_gate_binary(self) -> np.ndarray:
+        """1.0 when the cube is genuinely lifted above ``table_z + lift_margin`` (else 0.0)."""
+        cube_z = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, 2], dtype=self._np_dtype
+        )
+        thresh = self._np_dtype.type(self._reward_cfg.table_z) + self._np_dtype.type(
+            self._reward_cfg.lift_margin
+        )
+        return (cube_z > thresh).astype(self._np_dtype)
+
+    def _reward_lift_bonus(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        """Binary bonus for lifting the cube clear of the table (gated ``object_is_lifted``)."""
+        del info, fallen, success
+        return self._lift_gate_binary()
+
+    def _goal_track(self, info: dict[str, Any], std: float) -> np.ndarray:
+        """Lift-gated 3D goal tracking: ``1[lifted] * (1 - tanh(||cube - goal||_3D / std))``."""
+        cube = np.asarray(
+            self._backend.get_body_pos_w(self._cube_body_ids)[:, 0, :], dtype=self._np_dtype
+        )
+        goal = np.asarray(info["goal_pos"], dtype=self._np_dtype)
+        dist = np.linalg.norm(cube - goal, axis=-1)
+        s = max(float(std), 1e-06)
+        track = (1.0 - np.tanh(dist / s)).astype(self._np_dtype)
+        return (self._lift_gate_binary() * track).astype(self._np_dtype)
+
+    def _reward_goal_track_coarse(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        return self._goal_track(info, self._reward_cfg.goal_track_coarse_std)
+
+    def _reward_goal_track_fine(
+        self, info: dict[str, Any], fallen: np.ndarray, success: np.ndarray
+    ) -> np.ndarray:
+        del fallen, success
+        return self._goal_track(info, self._reward_cfg.goal_track_fine_std)
diff --git a/src/unilab/visualization/render_many.py b/src/unilab/visualization/render_many.py
index e8d86a209..b802f10ac 100644
--- a/src/unilab/visualization/render_many.py
+++ b/src/unilab/visualization/render_many.py
@@ -5,6 +5,8 @@
 for Motrix-only workflows.
 """
 
+from __future__ import annotations
+
 import math
 import os
 import subprocess
@@ -159,6 +161,17 @@ def _warn_render_unavailable() -> None:
     )
 
 
+def _apply_hide_geom_groups(vopt: mujoco.MjvOption, hide_geom_groups: list[int] | None) -> None:
+    """Disable rendering for the given MuJoCo geom group indices (each 0..mjNGROUP-1)."""
+    if not hide_geom_groups:
+        return
+    n = int(mujoco.mjNGROUP)
+    for g in hide_geom_groups:
+        gi = int(g)
+        if 0 <= gi < n:
+            vopt.geomgroup[gi] = 0
+
+
 def get_grid_offsets(num_envs, spacing=1.0):
     rows = int(math.ceil(math.sqrt(num_envs)))
     cols = int(math.ceil(num_envs / rows))
@@ -255,8 +268,9 @@ def render_frame_job(args):
     """
     Worker function to render a single frame.
     args: (state_batch, offsets, transparent, cam_distance, cam_elevation, cam_azimuth,
-           cam_lookat, marker_positions)
+           cam_lookat, marker_positions, hide_geom_groups)
     marker_positions: optional (num_envs, 3) world-frame positions for overlay spheres.
+    hide_geom_groups: optional list of geom group indices to hide in the renderer.
     """
     (
         state_batch,
@@ -267,6 +281,7 @@ def render_frame_job(args):
         cam_azimuth,
         cam_lookat,
         marker_positions,
+        hide_geom_groups,
     ) = args
 
     models = _worker_ctx["models"]
@@ -276,9 +291,11 @@ def render_frame_job(args):
         _replicable_terrain_geom_indices(m) for m in models
     ]
 
-    # Visual options
+    # Visual options (explicit defaults, then per-playback group visibility overrides)
     vopt = mujoco.MjvOption()
+    mujoco.mjv_defaultOption(vopt)
     vopt.flags[mujoco.mjtVisFlag.mjVIS_TRANSPARENT] = transparent
+    _apply_hide_geom_groups(vopt, hide_geom_groups)
     pert = mujoco.MjvPerturb()
     catmask_dynamic = mujoco.mjtCatBit.mjCAT_DYNAMIC
     catmask_static = mujoco.mjtCatBit.mjCAT_STATIC
@@ -451,6 +468,7 @@ def render_states_get_frames(
     cam_lookat=None,
     render_spacing=1.0,
     marker_positions_list=None,
+    hide_geom_groups=None,
 ):
     """
     Render a list of physics states and return the list of frames.
@@ -468,6 +486,7 @@ def render_states_get_frames(
         cam_lookat: Optional [x, y, z] lookat override for the free camera.
         render_spacing: Grid spacing used to offset each env in composed video frames.
         marker_positions_list: Optional list of (num_envs, 3) arrays for overlay spheres.
+        hide_geom_groups: Optional MuJoCo geom group indices to omit from rendering.
     Returns:
         List of numpy arrays (H, W, 3) (RGB)
     """
@@ -489,7 +508,17 @@ def render_states_get_frames(
 
     # Prepare arguments for each frame
     tasks = [
-        (s, offsets, False, cam_distance, cam_elevation, cam_azimuth, cam_lookat, m)
+        (
+            s,
+            offsets,
+            False,
+            cam_distance,
+            cam_elevation,
+            cam_azimuth,
+            cam_lookat,
+            m,
+            hide_geom_groups,
+        )
         for s, m in zip(
             state_list,
             marker_positions_list
@@ -569,6 +598,7 @@ def render_frame_tracking_job(args):
         cam_elevation,
         cam_azimuth,
         marker_positions,
+        hide_geom_groups,
     ) = args
 
     models = _worker_ctx["models"]
@@ -579,6 +609,8 @@ def render_frame_tracking_job(args):
     ]
 
     vopt = mujoco.MjvOption()
+    mujoco.mjv_defaultOption(vopt)
+    _apply_hide_geom_groups(vopt, hide_geom_groups)
     pert = mujoco.MjvPerturb()
     catmask_dynamic = mujoco.mjtCatBit.mjCAT_DYNAMIC
     catmask_static = mujoco.mjtCatBit.mjCAT_STATIC
@@ -720,6 +752,7 @@ def render_states_get_frames_tracking(
     cam_azimuth=90,
     render_spacing=1.0,
     marker_positions_list=None,
+    hide_geom_groups=None,
 ):
     """Render with camera tracking on a single primary environment.
 
@@ -735,6 +768,7 @@ def render_states_get_frames_tracking(
         cam_elevation: Camera elevation angle in degrees.
         cam_azimuth: Camera azimuth angle in degrees.
         render_spacing: Grid spacing for env layout.
+        hide_geom_groups: Optional MuJoCo geom group indices to omit from rendering.
     """
     if not state_list:
         print("No states to render.")
@@ -760,7 +794,17 @@ def render_states_get_frames_tracking(
     )
 
     tasks = [
-        (s, offsets, env_indices, primary_local_idx, cam_distance, cam_elevation, cam_azimuth, m)
+        (
+            s,
+            offsets,
+            env_indices,
+            primary_local_idx,
+            cam_distance,
+            cam_elevation,
+            cam_azimuth,
+            m,
+            hide_geom_groups,
+        )
         for s, m in zip(
             state_list,
             marker_positions_list
diff --git a/tests/utils/test_xml_utils.py b/tests/utils/test_xml_utils.py
index 27eb03d9b..04f77797f 100644
--- a/tests/utils/test_xml_utils.py
+++ b/tests/utils/test_xml_utils.py
@@ -94,7 +94,9 @@ def test_inject_mujoco_tracking_sensors_uses_mjspec_and_preserves_contract() ->
         baselink_name="pelvis",
     )
     try:
-        assert tracked_body_ids == list(range(1, len(valid_bnames) + 1))
+        # ``inject_mujoco_tracking_sensors`` still returns legacy placeholder ids; the
+        # MuJoCo backend re-resolves real body ids after ``MjModel.from_xml_path``.
+        assert len(tracked_body_ids) == len(valid_bnames)
         assert valid_bnames[0] == "pelvis"
 
         model = mujoco.MjModel.from_xml_path(tmp_xml)