A RRT-based motion planning of dual-arm robot for (Dis)assembly tasks

Abstract

This paper presents the manipulation planning of a dual-arm robot for an assembly task. To assemble the parts, two types of paths for the robot are required: assembly and re-grasping. The assembly path assembles and holds the objects with a fixed grasp, while the re-grasping path changes the robots grasp on objects depending on how the object was picked up and how it will be used. We implement a Rapidly-exploring Random Trees (RRT) algorithm to generate the assembly path and the re-grasping path in different ways to obtain the manipulation path of the dual-arm robot for the assembly task. Finally, both simple problems like linear puzzles and very complicated problems like alpha puzzles can be solved using the proposed manipulation planning algorithm. These examples are tested through simulation.