Motion Planning for an Underwater Mobile Manipulator by Exploiting Loose Coupling

Abstract

Intervention Autonomous Underwater Vehicle or I-AUV has recently started to grab researchers attention in the last 20 years. Only three I-AUVs have demonstrated autonomous manipulation skills: ALIVE, SAUVIM and GIRONA 500. While prior systems rely on variations of the task-priority redundancy control framework, our recent research showed preliminary results using motion planning for floating-based intervention in the presence of obstacles. With the increasing need for autonomously performing more complex manipulation tasks, two main challenges need to be addressed: the high-dimensionality of the system, and the motion coordination between the mobile base and the working arm. The latter challenge is of high importance if accurate execution is required, especially considering the floating nature of the AUV and the control challenges that come with it. Our approach relies on exploiting the loose coupling between the AUV and the arm. In particular we present an approach based on MR-MHA * (Multi-Representation, Multi-Heuristic A*), and we show how it can generate efficient trajectories by exploiting decoupling. We show for the first time the use of a search-based planner on a high-dimensional underwater manipulator. In addition, we support our claims with experimental analysis of the generated trajectories with respect to various metrics in different environments. Furthermore, we demonstrate the ability of our approach to conduct a full intervention mission in a realistic simulated underwater intervention environment.