A smoothing strategy for PRM paths application to six-axes MOTOMAN SV3X manipulator

摘要

This paper describes the use of the probabilistic motion planning technique SBL "single-query bidirectional probabilistic algorithm with lazy collision checking" or in motion planning for robot manipulators. We present a novel strategy to remedy the PRM "probabilistic roadmap" paths which are both excessively long and discontinuous in velocity and acceleration. The optimization of the path will be done first through coarse optimal lazy A* optimization and then through a fine cutting-triangles-edge one, the edges discontinuities are smoothed with cubic polynomials taking the robot's specific dynamic and cinematic constraints. The whole strategy is applied to the 6 axes robot Manipulator MOTOMAN SV3X.