Fast C-shape grasping for unknown objects

Conference paper (2017)

Authors

Q. Lei Robot Dynamics - Mechanical, Maritime and Materials Engineering
M. Wisse Robot Dynamics - Mechanical, Maritime and Materials Engineering
Research Group
Robot Dynamics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2017 Q. Lei, Jonathan Meijer, M. Wisse
DOI
help_outline
https://doi.org/10.1109/AIM.2017.8014068
Mechatronics Conferences
More Info
expand_more

Published Date

2017

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Robot Dynamics

Abstract

This paper identifies high-performing Open Motion Planning Library (OMPL) planners for grasp execution and simultaneously presents useful benchmark data. Four grasp executions were defined using a UR5 manipulator. The performance was measured by means of solved runs, computing time and path length. Based on the results, planners are recommended and the reasons are discussed.