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Article: Optimized vision-based robot motion planning from multiple demonstrations

TitleOptimized vision-based robot motion planning from multiple demonstrations
Authors
KeywordsVision-based motion planning
Path planning
FOV limits
Whole-arm collision avoidance
Issue Date2018
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0929-5593
Citation
Autonomous Robots, 2018, v. 42 n. 6, p. 1117-1132 How to Cite?
AbstractThis paper combines workspace models with optimization techniques to simultaneously address whole-arm collision avoidance, joint limits and camera field of view (FOV) limits for vision-based motion planning of a robot manipulator. A small number of user demonstrations are used to generate a feasible domain over which the whole robot arm can servo without violating joint limits or colliding with obstacles. Our algorithm utilizes these demonstrations to generate new feasible trajectories that keep the target in the camera’s FOV and achieve the desired view of the target (e.g., a pre-grasping location) in new, undemonstrated locations. To fulfill these requirements, a set of control points are selected within the feasible domain. Camera trajectories that traverse these control points are modeled and optimized using either quintic splines (for fast computation) or general polynomials (for better constraint satisfaction). Experiments with a seven degree of freedom articulated arm validate the proposed scheme.
Persistent Identifierhttp://hdl.handle.net/10722/272177
ISSN
2017 Impact Factor: 2.244
2015 SCImago Journal Rankings: 2.500
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShen, T-
dc.contributor.authorRadmard, S-
dc.contributor.authorChan, A-
dc.contributor.authorCroft, EA-
dc.contributor.authorChesi, G-
dc.date.accessioned2019-07-20T10:37:11Z-
dc.date.available2019-07-20T10:37:11Z-
dc.date.issued2018-
dc.identifier.citationAutonomous Robots, 2018, v. 42 n. 6, p. 1117-1132-
dc.identifier.issn0929-5593-
dc.identifier.urihttp://hdl.handle.net/10722/272177-
dc.description.abstractThis paper combines workspace models with optimization techniques to simultaneously address whole-arm collision avoidance, joint limits and camera field of view (FOV) limits for vision-based motion planning of a robot manipulator. A small number of user demonstrations are used to generate a feasible domain over which the whole robot arm can servo without violating joint limits or colliding with obstacles. Our algorithm utilizes these demonstrations to generate new feasible trajectories that keep the target in the camera’s FOV and achieve the desired view of the target (e.g., a pre-grasping location) in new, undemonstrated locations. To fulfill these requirements, a set of control points are selected within the feasible domain. Camera trajectories that traverse these control points are modeled and optimized using either quintic splines (for fast computation) or general polynomials (for better constraint satisfaction). Experiments with a seven degree of freedom articulated arm validate the proposed scheme.-
dc.languageeng-
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0929-5593-
dc.relation.ispartofAutonomous Robots-
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: http://dx.doi.org/[insert DOI]-
dc.subjectVision-based motion planning-
dc.subjectPath planning-
dc.subjectFOV limits-
dc.subjectWhole-arm collision avoidance-
dc.titleOptimized vision-based robot motion planning from multiple demonstrations-
dc.typeArticle-
dc.identifier.emailChesi, G: chesi@eee.hku.hk-
dc.identifier.authorityChesi, G=rp00100-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10514-017-9667-4-
dc.identifier.scopuseid_2-s2.0-85028752472-
dc.identifier.hkuros299103-
dc.identifier.volume42-
dc.identifier.issue6-
dc.identifier.spage1117-
dc.identifier.epage1132-
dc.identifier.isiWOS:000432977900001-
dc.publisher.placeUnited States-

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