Autonomous Underwater Vehicle-Manipulator Systems Path Planning with RRTAUVMS Algorithm

TL;DR

This paper introduces the RRTAUVMS algorithm, which enhances path planning efficiency for high-dimensional Autonomous Underwater Vehicle-Manipulator Systems operating in complex environments by integrating RRT with the system's kinematics.

Contribution

The paper presents a novel RRTAUVMS algorithm that improves path planning efficiency for AUVMS by combining RRT with kinematic models and handling redundant goal mappings.

Findings

Significantly improved path planning efficiency compared to traditional RRT.

Effective handling of redundant workspace and configuration space goals.

Applicable to complex underwater environments with obstacles.

Abstract

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.