Trajectory smoothing using jerk bounded shortcuts for service manipulator robots

Ran Zhao; Daniel Sidobre

IROS 2015poster22 citations

Trajectory smoothing using jerk bounded shortcuts for service manipulator robots

Abstract

This paper aims to smooth jerky trajectories for high-DOF manipulators with Soft Motion [1] shortcuts which are bounded in velocity, acceleration and jerk. The algorithm presented here iteratively picks two points on the trajectory and attempts to replace the intermediate trajectory with a shorter and collision-free segment. The objective of this algorithm is to shorten the execution time of an input trajectory as much as possible while retaining the feasibility. Simulation and real-world experimental results on reaching tasks in human environments show that this technique can generate smooth and collision-free motions for a KUKA Light-Weight Robot.

BibTeX

@inproceedings{iros2015_trajectorysmooth,
  title = {Trajectory smoothing using jerk bounded shortcuts for service manipulator robots},
  author = {Ran Zhao and Daniel Sidobre},
  booktitle = {IROS 2015},
  year = {2015}
}