Manipulator path planning using fusion algorithm of low difference sequence and rapidly exploring random tree

To solve the problem of low path planning efficiency of manipulator in high-dimensional joint space, a path planning method is proposed based on Sobol sequence and rapidly exploring random tree (RRT) algorithm. The proposed method firstly adopts Sobol sequences to replace the pseudo-random sequences for generating uniformly different sampling points in RRT. Secondly, a sampling pool is built to obtain the optimal sampling points during the sampling process, which improves the sampling quality and efficiency. Aiming at smoothing the planned path, a least square based polynomial fitting method is employed to fit the discrete points of each joint angle. The performance of the proposed method is evaluated in the two-dimensional space, and the results indicate that the improved method can quickly and steadily avoid obstacles to reach the target point. Finally, using AUBO-i5 manipulator as the prototype, the experimental study is carried out to verify the advantages of the proposed method in the application of the manipulator. © 2022, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.