Bidirectional RRT*-Based Path Planning for Tight Coordination of Dual Redundant Manipulators

Abstract

There are closed-chain constraints between the left manipulator and the right manipulator in tight coordination of the dual redundant manipulator. The existing planning algorithms suitable for loose coordination cannot be directly applied to tight coordination, as the planned path cannot satisfy the closed-chain constraints. To solve the above problem, a master-slave planning method based on bidirectional RRT* is proposed for dual redundant manipulators. Bidirectional RRT* is adopted to plan the path of the master manipulator. The path of the slave manipulator is calculated by terminal generalized velocity constraints instead of terminal position and posture constraints. Moreover, a local path replanning strategy is proposed to solve the problem that the planned path is actually not feasible due to the discontinuous joint path of the slave manipulator. The joint self-motion in the null space is utilized to keep the terminal position and posture of the slave manipulator unchanged. The proposed method is verified by simulations and experiments and the results show that it can solve the discontinuity problem, increase the success rate, shorten the planning time and satisfy closed-chain constraints. Therefore, the proposed method can be feasibly and effectively applied to the tight coordination of dual redundant manipulators.