2017 The Authors. Published by Elsevier B.V. Random bin picking is often considered primarily to be an object localization problem. However, the determination of a suitable grasp in a given situation is an equally important part of picking chaotically stored objects for which only few solutions exist. This paper presents a novel approach by representing the localized workpieces and possible grasps by a tree and using heuristic search to determine a feasible gripping solution in a short time. The proposed heuristic function is based on collision testing and a statistical evaluation of the likelihood for a collision-free grasp. Finally, the presented search method is experimentally validated.
%0 Journal Article
%1 Spenrath2017b
%A Spenrath, Felix
%A Pott, Andreas
%D 2017
%J Procedia CIRP
%K Bin Import180214;Feed;Robot myown; picking;
%P 606-611
%R 10.1016/j.procir.2016.06.015
%T Gripping Point Determination for Bin Picking Using Heuristic Search
%V 62
%X 2017 The Authors. Published by Elsevier B.V. Random bin picking is often considered primarily to be an object localization problem. However, the determination of a suitable grasp in a given situation is an equally important part of picking chaotically stored objects for which only few solutions exist. This paper presents a novel approach by representing the localized workpieces and possible grasps by a tree and using heuristic search to determine a feasible gripping solution in a short time. The proposed heuristic function is based on collision testing and a statistical evaluation of the likelihood for a collision-free grasp. Finally, the presented search method is experimentally validated.
@article{Spenrath2017b,
abstract = {\copyright 2017 The Authors. Published by Elsevier B.V. Random bin picking is often considered primarily to be an object localization problem. However, the determination of a suitable grasp in a given situation is an equally important part of picking chaotically stored objects for which only few solutions exist. This paper presents a novel approach by representing the localized workpieces and possible grasps by a tree and using heuristic search to determine a feasible gripping solution in a short time. The proposed heuristic function is based on collision testing and a statistical evaluation of the likelihood for a collision-free grasp. Finally, the presented search method is experimentally validated.},
added-at = {2018-02-14T08:37:06.000+0100},
author = {Spenrath, Felix and Pott, Andreas},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2b81c39d4df6084d657bd031995d856bb/andreaspott},
doi = {10.1016/j.procir.2016.06.015},
interhash = {4c28a058d645cab6316e6ed6ee4024df},
intrahash = {b81c39d4df6084d657bd031995d856bb},
issn = {22128271},
journal = {Procedia CIRP},
keywords = {Bin Import180214;Feed;Robot myown; picking;},
pages = {606-611},
timestamp = {2018-02-14T08:15:40.000+0100},
title = {Gripping Point Determination for Bin Picking Using Heuristic Search},
volume = 62,
year = 2017
}
