Cooperative Path planning for Redundant Dual-arm robot Using Low-dimensional Sample-based algorithm

Abstract

This research presents a low-dimensional sample-based path planning method for cooperative work of redundant dual-arm robot which has two humanlike 7 degrees of freedom robot arms. The main task for this system is to move an object from initial position to goal position while the end-effector of two arms concurrently grasp the object. To accomplish this work, we use redundant variables and absolute frame which is attached to the object. This method reduces the dimension of the sampling configuration space for the considering task 14 to 8. To more effectively find a path for the cooperative work of the system, we use a very simple equation that linearly changes the orientation of absolute frame from the start configuration to the goal configuration along a path. This equation further reduces the dimension of sampling configuration space 8 to 5. From this approach, we can effectively get a path for the cooperative work of humanoid type dual-arm robot using probabilistic roadmaps algorithm. To verify the proposed method, simulation program is developed and simulation is carried out with some specific setting. Simulation results show that proposed method effectively plans a cooperative path for the redundant dual-arm robot system.