LEO Rover ROS Model

LEO_Rover_ROS_Model is the standalone rover-platform repository used as the base for the CORODRO rover. It is the best place to understand the rover itself without the extra mission orchestration from IGLUNA-FC-Code.

Why This Repo Matters

This repository separates the reusable rover platform stack from the full field-campaign code. It gives students a cleaner place to study:

• the robot description and URDF model,
• Gazebo simulation,
• hardware bringup,
• teleoperation,
• RViz visualization,
• localization and navigation.

Added Value

• A student-friendly rover base stack that can be read independently from the full mission repository.
• A practical example of how the Leo Rover platform was extended for the CORODRO project.
• A compact ROS 1 navigation stack with well-separated packages and clear launch entry points.

Algorithms Used

• robot_localization EKF for wheel odometry and IMU fusion in leo_navigation/launch/odometry.launch.
• Madgwick IMU filtering through imu_filter_madgwick.
• slam_gmapping for online 2D SLAM.
• amcl for map-based localization.
• global_planner with use_dijkstra: true for global path planning.
• TrajectoryPlannerROS with dwa: true for local motion planning.
• Differential-drive simulation in Gazebo through leo_gazebo/src/differential_plugin.cpp.

Repository Map

• leo_description/: URDF, xacro files, meshes, and the robot_description launcher.
• leo_gazebo/: Gazebo launch files and the rover differential-drive plugin.
• leo_bringup/: bringup configuration for the physical rover stack.
• leo_navigation/: odometry fusion, SLAM, AMCL, and move_base configuration.
• leo_teleop/: joystick teleoperation.
• leo_viz/: RViz launch files and visualization profiles.
• leo_mast_bringup/: mast-related bringup configuration.
• leo_tests/: auxiliary launch files for tests and experiments.

Suggested Learning Path

1. Start with leo_description/launch/description.launch to understand the robot model.
2. Move to leo_gazebo/launch/leo_gazebo.launch to see the rover in simulation.
3. Study leo_navigation/launch/odometry.launch for sensor fusion.
4. Study leo_navigation/launch/gmapping.launch and leo_navigation/launch/amcl.launch for localization.
5. Finish with leo_navigation/launch/move_base.launch and leo_navigation/launch/navigation.launch for navigation.

Quick Start

1. Create a ROS 1 catkin workspace and place this repository in src/.
2. Install the ROS dependencies used by Gazebo, navigation, and teleoperation.
3. Build the workspace with catkin_make.
4. Launch the robot description with roslaunch leo_description description.launch.
5. Launch Gazebo with roslaunch leo_gazebo leo_gazebo.launch.
6. For navigation experiments, use the launch files in leo_navigation/.

Notes For Students

• leo_navigation is the best package to study first if your focus is localization and path planning.
• leo_description/old/ is historical material and should not be your default reference.
• The navigation demo nodes under leo_navigation/nodes/ are educational examples, not the main production path.
• Some navigation demo scripts are also present in IGLUNA-FC-Code; treat this repository as the cleaner rover-platform source.
• The navigation parameters are tuned for this rover and sensor suite, so use them as a baseline rather than universal defaults.

TODOs Before Retuning

• Validate leo_navigation/config/ekf_localization_node/ against the current IMU, wheel odometry topic, and frame tree before changing fusion parameters.
• Re-tune leo_navigation/config/slam_gmapping.yaml only after checking the live lidar or scan source used by the rover.
• Review the leo_navigation/config/move_base/ costmap and planner YAML files in simulation or hardware before changing navigation behavior.
• Re-validate leo_navigation/config/amcl.yaml on a representative map before adjusting localization thresholds or noise values.
• Keep leo_description/old/ as archive material unless you intentionally want to recover a past rover model.