다중 무인수상선의 협력항법을 위한 포텐셜장 기반의 편대 제어 기초 연구
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박정홍 | - |
dc.contributor.author | 이영준 | - |
dc.contributor.author | 정종대 | - |
dc.contributor.author | 강민주 | - |
dc.contributor.author | 최현택 | - |
dc.contributor.author | 최진우 | - |
dc.date.accessioned | 2021-12-08T07:41:33Z | - |
dc.date.available | 2021-12-08T07:41:33Z | - |
dc.date.issued | 20210625 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/2149 | - |
dc.description.abstract | This paper presents the potential field-based formation control framework considering a variation of the number of autonomous surface vehicles (ASVs). In this scheme, a virtual leader ASV is controlled to follow the predefined waypoints using the line-of-sight (LOS) approach and following ASVs are controlled to keep a relative range between the virtual leader ASV and each follower. For these, the APF (attractive potential field) for following the virtual leader ASV while keeping a relative range is designed, and the RPF (repulsive potential field) for collision avoidance between the vehicles is designed. In order to validate the feasibility of the proposed approach, simulations were performed and the results were briefly described. | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.title | 다중 무인수상선의 협력항법을 위한 포텐셜장 기반의 편대 제어 기초 연구 | - |
dc.title.alternative | Preliminary Study of Potential Field based Formation Control for Cooperative Navigation of Multiple Autonomous Surface Vehicles | - |
dc.type | Conference | - |
dc.citation.title | 제어로봇시스템학회 학술대회 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 2 | - |
dc.citation.conferenceName | 제어로봇시스템학회 학술대회 | - |
dc.citation.conferencePlace | 대한민국 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(34103) 대전광역시 유성구 유성대로1312번길 32042-866-3114
COPYRIGHT 2021 BY KOREA RESEARCH INSTITUTE OF SHIPS & OCEAN ENGINEERING. 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.