A POTENTIAL-BASED PATH PLANNING ALGORITHM FOR HYPER-REDUNDANT MANIPULATORS

Abstract

A novel collision avoidance algorithm based on the generalized potential model is proposed to solve the path-planning problem of hyper-redundant manipulators in 3D workspace. The approach computes repulsive force and torque between manipulator and obstacles by using the workspace information directly. A collision-free path for a manipulator can then be obtained by locally adjusting the manipulator configuration to search for minimum potential configurations using these forces and torques. The proposed approach is efficient since these potential gradients are analytically tractable. Furthermore, the proposed algorithm is also extended to dual-arm systems. Simulation results show that the proposed algorithm works well, in terms of computation time and collision avoidance.