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Article: Optimization-Based Framework for Excavation Trajectory Generation

TitleOptimization-Based Framework for Excavation Trajectory Generation
Authors
KeywordsMining robotics
robotics in construction
trajectory optimization
Issue Date2021
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE
Citation
IEEE Robotics and Automation Letters, 2021, v. 6 n. 2, p. 1479-1486 How to Cite?
AbstractIn thisletter, we present a novel optimization-based framework for autonomous excavator trajectory generation under task-specific constraints. Traditional excavation trajectory generators over-simplify the geometric trajectory parameterization thereby limiting the space for optimization. To expand the search space, we formulate a generic task specification for excavation by constraining the instantaneous motion of the bucket and adding a target-oriented constraint to control the amount of excavated soil. The trajectory is represented with a waypoint interpolating spline. Time intervals between waypoints are relaxed as variables to facilitate generating the time-optimal trajectory in one stage. Experiments on a real robot platform demonstrate that our method is adaptive to different terrain shapes and outperforms other optimal path planners in terms of the minimum joint length and minimum travel time.
Persistent Identifierhttp://hdl.handle.net/10722/300686
ISSN
2021 Impact Factor: 4.321
2020 SCImago Journal Rankings: 1.123
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYang, Y-
dc.contributor.authorLong, P-
dc.contributor.authorSong, X-
dc.contributor.authorPan, J-
dc.contributor.authorZhang, L-
dc.date.accessioned2021-06-18T14:55:33Z-
dc.date.available2021-06-18T14:55:33Z-
dc.date.issued2021-
dc.identifier.citationIEEE Robotics and Automation Letters, 2021, v. 6 n. 2, p. 1479-1486-
dc.identifier.issn2377-3766-
dc.identifier.urihttp://hdl.handle.net/10722/300686-
dc.description.abstractIn thisletter, we present a novel optimization-based framework for autonomous excavator trajectory generation under task-specific constraints. Traditional excavation trajectory generators over-simplify the geometric trajectory parameterization thereby limiting the space for optimization. To expand the search space, we formulate a generic task specification for excavation by constraining the instantaneous motion of the bucket and adding a target-oriented constraint to control the amount of excavated soil. The trajectory is represented with a waypoint interpolating spline. Time intervals between waypoints are relaxed as variables to facilitate generating the time-optimal trajectory in one stage. Experiments on a real robot platform demonstrate that our method is adaptive to different terrain shapes and outperforms other optimal path planners in terms of the minimum joint length and minimum travel time.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER481-ELE-
dc.relation.ispartofIEEE Robotics and Automation Letters-
dc.rightsIEEE Robotics and Automation Letters. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©20xx 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.subjectMining robotics-
dc.subjectrobotics in construction-
dc.subjecttrajectory optimization-
dc.titleOptimization-Based Framework for Excavation Trajectory Generation-
dc.typeArticle-
dc.identifier.emailPan, J: jpan@cs.hku.hk-
dc.identifier.authorityPan, J=rp01984-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/LRA.2021.3058071-
dc.identifier.scopuseid_2-s2.0-85101453793-
dc.identifier.hkuros323038-
dc.identifier.volume6-
dc.identifier.issue2-
dc.identifier.spage1479-
dc.identifier.epage1486-
dc.identifier.isiWOS:000623417800004-
dc.publisher.placeUnited States-

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