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  • 标题:Data Links Enhanced Relative Navigation for Robotic Formation Applications
  • 本地全文:下载
  • 作者:Ning Hao ; Rui Xing ; Haodi Yao
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:9484-9489
  • DOI:10.1016/j.ifacol.2020.12.2422
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWith the rapid development and widespread application of robotic formation, relative navigation problem has attracted extensive attention. In this paper, the relative navigation problem for robotic formation applications is investigated, for which, we provide a relative navigation method based on multi-sensor fusion. First of all, a data links enhanced relative navigation scheme is proposed. Secondly, the underlying estimation problem behind the relative navigation scheme is derived. Then, a recursive relative navigation algorithm based on maximum a posterior estimation is provided for different multi-sensor combinations. Finally, simulation experiments are performed to show the effectiveness of the proposed relative navigation method.
  • 关键词:KeywordsRobotic formationRelative navigationData linkState estimationMaximum a posterior estimation
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