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  • 标题:Real-time Local Path Planning for Intelligent Vehicle combining Tentacle Algorithm and B-spline Curve
  • 本地全文:下载
  • 作者:Zhuoren Li ; Lu Xiong ; Dequan Zeng
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:10
  • 页码:51-58
  • DOI:10.1016/j.ifacol.2021.10.140
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe obstacle-avoidance problem of intelligent vehicles is one of the challenges that we face in path planning. In order to tackle it, this paper proposes a real-time path planning approach based on tentacle algorithm and B-spline curve. In this approach, firstly, some virtual tentacles are built to represent the precalculated paths of the ego vehicle at a current speed. Secondly, it selects the best tentacle path among them, which is required to provide a safe driving direction and sampling area for generating B-spline paths. When the vehicle drives along the best tentacle path, the B-spline path is generated according to the sampling area. Finally, the designed path is formed by segments of the best tentacle and a B-spline curve. Compared with other sampling-based path sets approaches, using the proposed approach needs shorter reaction time. Simulation and experiment results verify the real-time performance and effectiveness of the algorithm of local path planning.
  • 关键词:KeywordsPath planningIntelligent vehicleB-spline curvesSampling-based method
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