Robust and Autonomous Stereo Visual-Inertial Navigation for Non-Holonomic Mobile Robots
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chae, Hee-Won | - |
dc.contributor.author | Choi, Ji-Hoon | - |
dc.contributor.author | Song, Jae-Bok | - |
dc.date.accessioned | 2021-08-30T15:12:58Z | - |
dc.date.available | 2021-08-30T15:12:58Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2020-09 | - |
dc.identifier.issn | 0018-9545 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/53281 | - |
dc.description.abstract | Unlike micro aerial vehicles, most mobile robots have non-holonomic constraints, which makes lateral movement impossible. Consequently, the vision-based navigation systems that perform accurate visual feature initialization by moving the camera to the side to ensure a sufficient parallax of the image are degraded when applied to mobile robots. Generally, to overcome this difficulty, a motion model based on wheel encoders mounted on a mobile robot is used to predict the pose of a robot, but it is difficult to cope with errors caused by wheel slip or inaccurate wheel calibration. In this study, we propose a robust autonomous navigation system that uses only a stereo inertial sensor and does not rely on wheel-based dead reckoning. The observation model of the line feature modified with vanishing-points is applied to the visual-inertial odometry along with the point features so that a mobile robot can perform robust pose estimation during autonomous navigation. The proposed algorithm, i.e., keyframe-based autonomous visual-inertial navigation (KAVIN) supports the entire navigation system and can run onboard without an additional graphics processing unit. A series of experiments in a real environment indicated that the KAVIN system provides robust pose estimation without wheel encoders and prevents the accumulation of drift error during autonomous driving. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | HISTOGRAM | - |
dc.title | Robust and Autonomous Stereo Visual-Inertial Navigation for Non-Holonomic Mobile Robots | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Song, Jae-Bok | - |
dc.identifier.doi | 10.1109/TVT.2020.3004163 | - |
dc.identifier.scopusid | 2-s2.0-85094191880 | - |
dc.identifier.wosid | 000577995300030 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.69, no.9, pp.9613 - 9623 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | - |
dc.citation.title | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | - |
dc.citation.volume | 69 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 9613 | - |
dc.citation.endPage | 9623 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Transportation Science & Technology | - |
dc.subject.keywordPlus | HISTOGRAM | - |
dc.subject.keywordAuthor | Mobile robots | - |
dc.subject.keywordAuthor | Cameras | - |
dc.subject.keywordAuthor | Navigation | - |
dc.subject.keywordAuthor | Wheels | - |
dc.subject.keywordAuthor | Feature extraction | - |
dc.subject.keywordAuthor | Robot vision systems | - |
dc.subject.keywordAuthor | Autonomous navigation | - |
dc.subject.keywordAuthor | visual-inertial systems | - |
dc.subject.keywordAuthor | keyframes | - |
dc.subject.keywordAuthor | wheeled mobile robots | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea 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.