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.
翻译:自动水下车辆操纵系统(AUVMS)是海洋勘探的新工具,本文讨论了AUVMS路径规划问题。AUVMS是一个高维系统,惯性分布差异很大,也是在复杂环境中工作,有障碍。通过将快速勘探随机树算法与AUVMS运动模型相结合,拟议的RRTAUMS算法可以在配置空间(C-空间)中随机抽样,并将树直接种植到任务空间的工作空间目标上。RRTAVMS还可以处理工作空间规划目标和配置空间目标的冗余绘图。与传统的RRT算法相比,AVMS路径规划的效率可以大大提高。