Trajectory generation of wheeled mobile robot using convolution method
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Junghoon | - |
dc.contributor.author | Choi, Youngjin | - |
dc.date.accessioned | 2021-06-23T12:03:45Z | - |
dc.date.available | 2021-06-23T12:03:45Z | - |
dc.date.created | 2021-01-22 | - |
dc.date.issued | 2011-11 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/39093 | - |
dc.description.abstract | This paper suggests a trajectory generation method using convolution operation for wheeled mobile robots. To be smooth (infinitely differentiable) trajectory generation for wheeled mobile robot, a curvature is utilized in this paper. It makes possible that mobile robots have arbitrary final position and heading angle. After making path to be followed, the trajectory is designed in such a way to satisfy given constraints such as maximum velocity, maximum acceleration and maximum jerk. Also, convolution method is able to guarantee the trajectory to satisfy given constraints. Since mobile robots are equipped with driving motors as control inputs, ultimately, motor's specifications are utilized for convolution trajectory generation. © 2011 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.title | Trajectory generation of wheeled mobile robot using convolution method | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Youngjin | - |
dc.identifier.doi | 10.1109/URAI.2011.6145999 | - |
dc.identifier.scopusid | 2-s2.0-84863165002 | - |
dc.identifier.bibliographicCitation | URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, pp.371 - 374 | - |
dc.relation.isPartOf | URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence | - |
dc.citation.title | URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence | - |
dc.citation.startPage | 371 | - |
dc.citation.endPage | 374 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | constraint | - |
dc.subject.keywordPlus | Control inputs | - |
dc.subject.keywordPlus | curvature | - |
dc.subject.keywordPlus | Driving motors | - |
dc.subject.keywordPlus | Heading angles | - |
dc.subject.keywordPlus | Maximum acceleration | - |
dc.subject.keywordPlus | Maximum velocity | - |
dc.subject.keywordPlus | trajectory generation | - |
dc.subject.keywordPlus | Trajectory generation method | - |
dc.subject.keywordPlus | Wheeled mobile robot | - |
dc.subject.keywordPlus | Artificial intelligence | - |
dc.subject.keywordPlus | Convolution | - |
dc.subject.keywordPlus | Mobile robots | - |
dc.subject.keywordPlus | Trajectories | - |
dc.subject.keywordAuthor | constraint | - |
dc.subject.keywordAuthor | convolution | - |
dc.subject.keywordAuthor | curvature | - |
dc.subject.keywordAuthor | mobile robot | - |
dc.subject.keywordAuthor | trajectory generation | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/6145999/ | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.