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Dexterous grasping under shape uncertainty
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-4132-1217
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
2016 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 75, 352-364 p.Article in journal (Refereed) Published
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Text
Abstract [en]

An important challenge in robotics is to achieve robust performance in object grasping and manipulation, dealing with noise and uncertainty. This paper presents an approach for addressing the performance of dexterous grasping under shape uncertainty. In our approach, the uncertainty in object shape is parametrized and incorporated as a constraint into grasp planning. The proposed approach is used to plan feasible hand configurations for realizing planned contacts using different robotic hands. A compliant finger closing scheme is devised by exploiting both the object shape uncertainty and tactile sensing at fingertips. Experimental evaluation demonstrates that our method improves the performance of dexterous grasping under shape uncertainty.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 75, 352-364 p.
Keyword [en]
Dexterous grasping, Shape uncertainty, Grasp control, Grasp learning
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-181376DOI: 10.1016/j.robot.2015.09.008ISI: 000367763400018Scopus ID: 2-s2.0-84945388463OAI: oai:DiVA.org:kth-181376DiVA: diva2:900294
Funder
EU, European Research Council, 288533 ROBOHOW.COG.
Note

QC 20160203

Available from: 2016-02-03 Created: 2016-02-01 Last updated: 2016-02-03Bibliographically approved

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Citation style
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  • vancouver
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  • nn-NB
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  • Other locale
More languages
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