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Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review
Department of Mathematics, Faculty of Science, UNAM Universidad Nacional Autonoma de Mexico, Ciudad de México, Mexico.
Örebro University, School of Science and Technology. (Autonomous Mobile Manipulation Laboratory, Centre for Applied Autonomous Sensor Systems)ORCID iD: 0000-0001-6254-5135
PRISMA Laboratory, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.
Robotics, Learning and Perception Laboratory, Centre for Autonomous Systems, EECS, KTH Royal Institute of Technology, Stockholm, Sweden.
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2020 (English)In: Frontiers in Robotics and AI, E-ISSN 2296-9144, Vol. 7, article id 82Article, review/survey (Refereed) Published
Abstract [en]

Manipulation of deformable objects has given rise to an important set of open problems in the field of robotics. Application areas include robotic surgery, household robotics, manufacturing, logistics, and agriculture, to name a few. Related research problems span modeling and estimation of an object's shape, estimation of an object's material properties, such as elasticity and plasticity, object tracking and state estimation during manipulation, and manipulation planning and control. In this survey article, we start by providing a tutorial on foundational aspects of models of shape and shape dynamics. We then use this as the basis for a review of existing work on learning and estimation of these models and on motion planning and control to achieve desired deformations. We also discuss potential future lines of work.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2020. Vol. 7, article id 82
Keywords [en]
deformable objects, shape representation, learning of deformation, control of deformable objects, registration of shape deformation, tracking of deformation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-86838DOI: 10.3389/frobt.2020.00082ISI: 000576838200001PubMedID: 33489308Scopus ID: 2-s2.0-85091905373OAI: oai:DiVA.org:oru-86838DiVA, id: diva2:1479433
Funder
VinnovaSwedish Research Council FormasSwedish Energy AgencySwedish Research CouncilSwedish Foundation for Strategic Research
Note

Funding Agencies:

SIP-STRIM project TracMac  2017-02205

POR FESR 2014-2020 Italian National programme within BARTOLO project  CUP B41C17000090007

PNR 2015-2020 Italian National programme within PROSCAN project  CUP E26C18000170005

Available from: 2020-10-27 Created: 2020-10-27 Last updated: 2021-01-28Bibliographically approved

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Güler, Püren

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