Autonomous Underwater Vehicle-Manipulator Systems Path Planning with RRTAUVMS Algorithm
This addresses path planning for AUVMS, an incremental improvement for ocean exploration robotics.
The paper tackles the path planning problem for Autonomous Underwater Vehicle-Manipulator Systems (AUVMS) in complex ocean environments by proposing the RRTAUVMS algorithm, which integrates RRT with AUVMS kinematics to improve efficiency compared to traditional RRT.
Autonomous Underwater Vehicle-Manipulator systems (AUVMS) is a new tool for ocean exploration, the AUVMS path planning problem is addressed in this paper. AUVMS is a high dimension system with a large difference in inertia distribution, also it works in a complex environment with obstacles. By integrating the rapidly-exploring random tree(RRT) algorithm with the AUVMS kinematics model, the proposed RRTAUVMS algorithm could randomly sample in the configuration space(C-Space), and also grow the tree directly towards the workspace goal in the task space. The RRTAUVMS can also deal with the redundant mapping of workspace planning goal and configuration space goal. Compared with the traditional RRT algorithm, the efficiency of the AUVMS path planning can be significantly improved.