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文章基本信息

  • 标题:Planning in Dynamic and Partially Unknown Environments
  • 本地全文:下载
  • 作者:Kristina Miller ; Chuchu Fan ; Sayan Mitra
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:5
  • 页码:169-174
  • DOI:10.1016/j.ifacol.2021.08.493
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractMotion planning in dynamic and partially unknown environments is a difficult problem requiring both perception and control components. We propose a solution to the control component while cleanly abstracting perception. We show that this clean abstraction can be used to synthesize verifiably safe reference trajectories using a combination of reachability analysis and Mixed Integer Linear Programming. Experiments with a prototype implementation of this algorithm show promise as it has subsecond synthesis performance for nonlinear vehicle models in scenarios with hundred plus obstacles on standard hardware.
  • 关键词:Keywordscontrol synthesisswitched systemscyberphysical systemsverificationautonomy
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