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Abstract
Evaluation of grasps on deformable 3D objects is a little-studied problem, even if the applicability of rigid object grasp quality measures for deformable ones is an open question. A central issue with most quality measures is their dependence on contact points, which for deformable objects depend on the deformations. This paper proposes a grasp quality measure for deformable objects that uses information about object deformation to calculate the grasp quality. Grasps are evaluated by simulating the deformations during grasping and predicting the contacts between the gripper and the grasped object. The contact information is then used as input for a new grasp quality metric to quantify the grasp quality. The approach is benchmarked against two classical rigid-body quality metrics on over 600 grasps in the Isaac gym simulation and over 50 real-world grasps. Experimental results show an average improvement of 18% in the grasp success rate for deformable objects compared to the classical rigid-body quality metrics. Furthermore, the proposed approach is approximately fifteen times faster to calculate than the shake task, which, to date, is one of the most reliable approaches to quantify a grasp on a deformable object.
Original language | English |
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Title of host publication | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 |
Publisher | IEEE |
Pages | 3123-3129 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-6654-7927-1 |
DOIs | |
Publication status | Published - 26 Dec 2022 |
MoE publication type | A4 Conference publication |
Event | IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS - Duration: 1 Jan 1900 → … |
Publication series
Name | Proceedings of the IEEE/RSJ international conference on intelligent robots and systems |
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ISSN (Electronic) | 2153-0866 |
Conference
Conference | IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS |
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Abbreviated title | IROS |
Period | 01/01/1900 → … |
Keywords
- Robotic grasping
- Deformable objects
- Grasp Quality Metrics
- grasp analysis approach
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Dive into the research topics of 'A Novel Simulation-Based Quality Metric for Evaluating Grasps on 3D Deformable Objects'. Together they form a unique fingerprint.Projects
- 2 Finished
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-: Interactive Perception-Action-Learning for Modelling Objects
Kyrki, V. (Principal investigator)
01/05/2019 → 30/11/2022
Project: Academy of Finland: Other research funding
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ROSE: Robots and the Future of Welfare Services
Kyrki, V. (Principal investigator)
01/01/2018 → 30/04/2021
Project: Academy of Finland: Strategic research funding