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Paper ThCT4.2

Zhao, Ran (University of Toulouse), Sidobre, Daniel (University of Toulouse)

Trajectory Smoothing Using Jerk Bounded Shortcuts for Service Manipulator Robots

Scheduled for presentation during the Regular session "Motion and Trajectory Generation" (ThCT4), Thursday, October 1, 2015, 11:35−11:50, Saal C1+C2

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 20, 2019

Keywords Motion and Trajectory Generation, Motion Planning for Manipulators, Motion and Path Planning

Abstract

This paper aims to smooth jerky trajectories for high-DOF manipulators with Soft Motion 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.

 

 

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