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Proceedings Paper

Fast grasping of unknown objects using cylinder searching on a single point cloud
Author(s): Qujiang Lei; Martijn Wisse
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Paper Abstract

Grasping of unknown objects with neither appearance data nor object models given in advance is very important for robots that work in an unfamiliar environment. The goal of this paper is to quickly synthesize an executable grasp for one unknown object by using cylinder searching on a single point cloud. Specifically, a 3D camera is first used to obtain a partial point cloud of the target unknown object. An original method is then employed to do post treatment on the partial point cloud to minimize the uncertainty which may lead to grasp failure. In order to accelerate the grasp searching, surface normal of the target object is then used to constrain the synthetization of the cylinder grasp candidates. Operability analysis is then used to select out all executable grasp candidates followed by force balance optimization to choose the most reliable grasp as the final grasp execution. In order to verify the effectiveness of our algorithm, Simulations on a Universal Robot arm UR5 and an under-actuated Lacquey Fetch gripper are used to examine the performance of this algorithm, and successful results are obtained.

Paper Details

Date Published: 17 March 2017
PDF: 9 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034108 (17 March 2017); doi: 10.1117/12.2268422
Show Author Affiliations
Qujiang Lei, Technische Univ. Delft (Netherlands)
Martijn Wisse, Technische Univ. Delft (Netherlands)

Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

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