Fast grasping of unknown objects using cylinder searching on a single point cloud

Fast grasping of unknown objects using cylinder searching on a single point cloud

Lei, Q. (TU Delft Robot Dynamics)
Wisse, M. (TU Delft Robot Dynamics)

Verikas, Antanas (editor)
Radeva, Petia (editor)
Nikolaev, Dmitry P. (editor)
Zhang, Wei (editor)
Zhou, Jianhong (editor)

2017

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.

unknown object grasping
cylinder searching
single point cloud
3D vision
robot

http://resolver.tudelft.nl/uuid:856c5ca3-eb3d-48b0-9333-400024e1a7e7

https://doi.org/10.1117/12.2268422

SPIE, Bellingham, WA, USA

978-1-510611313

Ninth International Conference on Machine Vision: ICMV 2016

ICMV 2016: 9th International Conference on Machine Vision, 2016-11-18 → 2016-11-20, Nice, France

Proceedings of SPIE, 1605-7422, 10341

Institutional Repository

conference paper

© 2017 Q. Lei, M. Wisse