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Caging Complex Objects with Geodesic Balls
Universität Stuttgart. (Machine Learning and Robotics Lab)
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-1114-6040
Universität Stuttgart. (Machine Learning and Robotics Lab)
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2965-2953
2013 (English)In: Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), IEEE , 2013, 2999-3006 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.

Place, publisher, year, edition, pages
IEEE , 2013. 2999-3006 p.
Series
IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858
Keyword [en]
Contact surface, Extract informations, Gaussian curvatures, Hand kinematics, Real-world objects, Realistic robots, Robustness to noise, Scoring functions
National Category
Computer Science Robotics
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-129496DOI: 10.1109/IROS.2013.6696781ISI: 000331367403011Scopus ID: 2-s2.0-84893720249ISBN: 978-1-4673-6358-7 (print)OAI: oai:DiVA.org:kth-129496DiVA: diva2:655671
Conference
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) November 3-7, 2013. Tokyo, Japan
Funder
EU, FP7, Seventh Framework Programme, IST-FP7- 270436
Note

QC 20140128

Available from: 2013-10-13 Created: 2013-09-30 Last updated: 2014-04-14Bibliographically approved

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Pokorny, Florian T.Kragic, Danica

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