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dc.contributor.authorRosell Gratacòs, Jan
dc.contributor.authorSaoji, Siddhant
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2021-02-09T11:05:31Z
dc.date.available2021-02-09T11:05:31Z
dc.date.issued2020
dc.identifier.citationRosell, J.; Saoji, S. Flexibly configuring task and motion planning problems for mobile manipulators*. A: IEEE International Conference on Emerging Technologies and Factory Automation. "2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): Proceedings: Vienna, Austria - Hybrid: 08-11 September, 2020". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 1285-1288. ISBN 978-1-7281-8957-4. DOI 10.1109/ETFA46521.2020.9212086.
dc.identifier.isbn978-1-7281-8957-4
dc.identifier.urihttp://hdl.handle.net/2117/337136
dc.description© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
dc.description.abstractRobotic manipulation requires the planning at a symbolic level (task planning) and at a geometric level (motion planning). This paper presents a planning framework for both levels of planning that includes an easy way to configure their interconnection. Motion planning is done using The Kautham Project, which is equipped with the Open Motion Planning Library suite of sampling-based motion planners, and task planning is done using the Fast Forward task planner. Both planning levels can be accessed through Robotic Operating System interfaces using services. A client program then uses these task and motion planning services and an XML configuration file that defines the linkage between symbolic actions and geometric values, to compute the sequence of feasible robot motions that allow to successfully execute a manipulation task. An illustrative example using the TIAGo mobile manipulator in a kitchen environment is presented where the flexibility in configuring different instances of manipulation tasks is shown.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject.lcshMobile robots
dc.subject.otherRobotic manipulation
dc.subject.otherTask planning
dc.subject.otherMotion planning
dc.titleFlexibly configuring task and motion planning problems for mobile manipulators*
dc.typeConference lecture
dc.subject.lemacRobots mòbils
dc.contributor.groupUniversitat Politècnica de Catalunya. SIR - Service and Industrial Robotics
dc.identifier.doi10.1109/ETFA46521.2020.9212086
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9212086
dc.rights.accessOpen Access
local.identifier.drac29706825
dc.description.versionPostprint (author's final draft)
local.citation.authorRosell, J.; Saoji, S.
local.citation.contributorIEEE International Conference on Emerging Technologies and Factory Automation
local.citation.publicationName2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): Proceedings: Vienna, Austria - Hybrid: 08-11 September, 2020
local.citation.startingPage1285
local.citation.endingPage1288


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain