Planning optimal minimum-jerk trajectories for redundant robots

Abstract

In this paper, a minimum-jerk trajectory planning approach for redundant manipulators is presented. The proposed approach leverages not only the optimization of the time intervals between each of the way points of the assigned path, but also the optimal positions of a selected robot joint to reduce the jerk of the robot end-effector. This multi-stage optimization strategy is validated through extensive numerical simulations and experimental tests on a robot with seven degrees of freedom performing a pick-and-place motion. The results of the tests, supported by accelerometer measurements of the vibrations of the robot end-effector, prove the performance of the proposed approach in reducing both the acceleration and the jerk levels of the redundant manipulator in comparison with a state-of-the-art trajectory planning technique.