Degeneracy-Aware Full-Pose Path Planning Strategy for Robot Manipulator

Abstract

In this article, we present a novel full-pose path planning strategy with degenerate direction avoidance for robot manipulators. Effort seeks to define an efficient multiobjective cost function for finding an optimal path in task space by minimizing the path length, and, meanwhile, maximizing orthogonality to the degenerate direction of the path. Since a robot manipulator by nature is a noncommensurate system, the unit dual quaternion is used to unify the pose representation and formulate the cost function of path length. Additionally, to justify the robot’s ability to maneuver, another cost evaluation of orthogonality is developed on the basis of the analytical Jacobian matrix decomposition. The optimized rapidly exploring random tree (RRT*) is, then, applied to execute the synthesized cost function in planning a path for a six-degree-of-freedom (6-DOF) FANUC-M-20iA industrial robot. By comparing with two relevant path planning methods, simulation analysis results illustrate the superior performance of the proposed path planning approach in terms of path direction and joint change.