This is the code of my master thesis Motion Planning and Control for Fully Submerged Hydrofoil Vessels
Hydrofoil vessels are emerging as a promising solution for sustainable, high- speed waterborne transportation. By reducing hydrodynamic drag through hull elevation, they enable energy-efficient operation. Fully submerged hydrofoils offer superior performance compared to surface-piercing designs but introduce significant challenges for control. They have highly nonlinear dynamics, six degrees of freedom, and strict constraints for stability. These characteristics demand advanced motion planning and control strategies capable of operating in dynamic environments. This thesis investigates motion planning and control through the development of a novel dynamic model of a fully submerged hydrofoil vessel, qualitatively validated using a physical scale model. On this foundation, sampling-based motion planning algorithms, including Rapidly-exploring Random Trees (RRT) and Stable Sparse-RRT (SST), are studied for their ability to generate feasible trajectories under hydrofoil-specific dynamics and obstacle constraints. For tra jectory-following of the planned motion, full-state feedback control methods are explored, focusing on Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC).