A visual localization technique for unmanned ground and aerial robots
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shim, J.H. | - |
dc.contributor.author | Cho, Y.I. | - |
dc.date.available | 2020-02-27T20:42:24Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6658 | - |
dc.description.abstract | In this paper, we propose a technique for UGV robot's localization using map data of an UAV(Unmanned Aerial Vehicle) with RGB-D camera. UGV has a large loading capacity and a long battery life, but it has limited movement. On the other hand, UAV is free to move but has a small loading capacity and a short battery life. In case of UAV SLAM(Simultaneous Localization And Mapping), location recognition error occurs due to the influence of terrain and obstacles. Since odometry information of UAV SLAM is more complicated than UGV SLAM, location recognition error is accumulated when continuous position recognition is performed after generating map data. Therefore, we proposed a technique to make the UGV SLAM possible by sharing map data of two robots after making map data by using UAV which is relatively mobile. It is useful to complement each other's disadvantages between UAV and UGV. And we presented the advantages of RGB-D camera based SLAM by comparing the accuracy of a SLAM using 2D-camera and 2D LRF (Laser Range Finder) SLAM. Through a series of experiments, the effectiveness of the proposed UAV SLAM using RGB-D cameras was introduced by comparing UAV SLAM with UGV SLAM with RGB-D camera. © 2017 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.relation.isPartOf | Proceedings - 2017 1st IEEE International Conference on Robotic Computing, IRC 2017 | - |
dc.subject | Cameras | - |
dc.subject | Electric batteries | - |
dc.subject | Intelligent vehicle highway systems | - |
dc.subject | Mobile robots | - |
dc.subject | Range finders | - |
dc.subject | Robots | - |
dc.subject | Secondary batteries | - |
dc.subject | Unmanned aerial vehicles (UAV) | - |
dc.subject | Laser range finders | - |
dc.subject | Localization | - |
dc.subject | Location recognition | - |
dc.subject | Position recognition | - |
dc.subject | SLAM | - |
dc.subject | SLAM (simultaneous localization and mapping) | - |
dc.subject | UAV (unmanned aerial vehicle) | - |
dc.subject | Visual localization | - |
dc.subject | Robotics | - |
dc.title | A visual localization technique for unmanned ground and aerial robots | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000411203500066 | - |
dc.identifier.doi | 10.1109/IRC.2017.71 | - |
dc.identifier.bibliographicCitation | Proceedings - 2017 1st IEEE International Conference on Robotic Computing, IRC 2017, pp.399 - 403 | - |
dc.identifier.scopusid | 2-s2.0-85020210866 | - |
dc.citation.endPage | 403 | - |
dc.citation.startPage | 399 | - |
dc.citation.title | Proceedings - 2017 1st IEEE International Conference on Robotic Computing, IRC 2017 | - |
dc.contributor.affiliatedAuthor | Cho, Y.I. | - |
dc.type.docType | Proceedings Paper | - |
dc.subject.keywordAuthor | Localization | - |
dc.subject.keywordAuthor | Mobile robot | - |
dc.subject.keywordAuthor | RGB-D | - |
dc.subject.keywordAuthor | SLAM | - |
dc.subject.keywordAuthor | UAV | - |
dc.subject.keywordAuthor | UGV | - |
dc.subject.keywordPlus | Cameras | - |
dc.subject.keywordPlus | Electric batteries | - |
dc.subject.keywordPlus | Intelligent vehicle highway systems | - |
dc.subject.keywordPlus | Mobile robots | - |
dc.subject.keywordPlus | Range finders | - |
dc.subject.keywordPlus | Robots | - |
dc.subject.keywordPlus | Secondary batteries | - |
dc.subject.keywordPlus | Unmanned aerial vehicles (UAV) | - |
dc.subject.keywordPlus | Laser range finders | - |
dc.subject.keywordPlus | Localization | - |
dc.subject.keywordPlus | Location recognition | - |
dc.subject.keywordPlus | Position recognition | - |
dc.subject.keywordPlus | SLAM | - |
dc.subject.keywordPlus | SLAM (simultaneous localization and mapping) | - |
dc.subject.keywordPlus | UAV (unmanned aerial vehicle) | - |
dc.subject.keywordPlus | Visual localization | - |
dc.subject.keywordPlus | Robotics | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Robotics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Robotics | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon 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.