Obstacle-avoidance path planning based on the improved artificial potential field for a 5 degrees of freedom bending robot

Abstract

Path planning is a key technique used in the operation of bending robots. In this paper, an obstacle-avoidance path-planning method of a 5 degrees of freedom (5 DOF) bending robot based on improved artificial potential field is proposed. Firstly, a connecting-rod coordinate system of the 5 DOF Cartesian bending robot is established to determine an equation of motion trajectory of the bending robot. Secondly, in view of the problem of the local minimum in the artificial potential field (APF) method and the failure of path planning, an improved APF path-planning method based on a rapidly exploring random tree (RRT) algorithm is proposed, which reduces the length of the path and enhances path smoothness. Finally, through simulation and obstacle-avoidance experiments on the path of a mechanical arm, effective path planning based on the improved APF method is verified. The experimental results show that the proposed path-planning method can plan an optimal path and meet the technical requirements of bending robot operations.