Path planning for AUV docking in confined environments

Sammanfattning

In this work, we address the problem of path planning for soft docking scenarios involving an Autonomous Underwater Vehicle (AUV) operating in confined environments, where unconventional maneuvers are required to reach a specified goal due to the nonholonomic nature of the robot. The planner must not only guide the robot to the final position but also satisfy constraints such as achieving zero velocity and a desired orientation, ensuring proper interaction with the docking station. Our proposed approach builds on the A Star (A*) algorithm, using motion primitives to dynamically grow the search tree. Additionally, we modify the cost function from the classical A* formulation to also evaluate the current orientation and velocity of the robot beyond the current position with respect to the goal. Our method improves upon the standard A* algorithm in such confined environments for the specific AUV under consideration, enabling the generation of complex trajectories that align the robot with the desired final state.