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A Novel Simulation-Based Quality Metric for Evaluating Grasps on 3D Deformable Objects
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL. Aalto Univ, Sch Elect Engn, Dept Elect Engn & Automat, Intelligent Robot Grp, Espoo, Finland..ORCID iD: 0000-0003-2296-6685
Aalto Univ, Sch Elect Engn, Dept Elect Engn & Automat, Intelligent Robot Grp, Espoo, Finland..
Aalto Univ, Sch Elect Engn, Dept Elect Engn & Automat, Intelligent Robot Grp, Espoo, Finland..
2022 (English)In: 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 3123-3129Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. p. 3123-3129
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-325035DOI: 10.1109/IROS47612.2022.9981169ISI: 000908368202066Scopus ID: 2-s2.0-85146351855OAI: oai:DiVA.org:kth-325035DiVA, id: diva2:1746749
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), OCT 23-27, 2022, Kyoto, JAPAN
Note

QC 20230329

Available from: 2023-03-29 Created: 2023-03-29 Last updated: 2025-02-09Bibliographically approved

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Lundell, Jens

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  • apa
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