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Robust and fast generation of top and side grasps for unknown objects

Brice Denoun, Beatriz Leon, Claudio Zito, Rustam Stolkin, Lorenzo Jamone, Miles Hansard

Year
2019
Access
Open access

Abstract

In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camera, and of selecting the most promising one. We demonstrate the effectiveness of our approach on a picking scenario on a real robot platform. Our approach has shown to be more reliable than another recent geometry-based method considered as baseline [7] in terms of grasp stability, by increasing the successful grasp attempts by a factor of six.

Keywords

cs.ROcs.CV

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