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

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, M. Wisse
DOI
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https://doi.org/10.1117/12.2268422
Robot Unknown object grasping 3D vision Cylinder searching Single point cloud
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Published Date

2017

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Robot Dynamics

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.

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