文章基本信息

标题：Warm-Started Optimized Trajectory Planning for ASVs
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作者：Glenn Bitar ; Vegard N. Vestad ; Anastasios M. Lekkas 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：21
页码：308-314
DOI：10.1016/j.ifacol.2019.12.325
语种：English
出版社：Elsevier
摘要：We consider warm-started optimized trajectory planning for autonomous surface vehicles (ASVs) by combining the advantages of two types of planners: an A* implementation that quickly finds the shortest piecewise linear path, and an optimal control-based trajectory planner. A nonlinear 3-degree-of-freedom underactuated model of an ASV is considered, along with an objective functional that promotes energy-efficient and readily observable maneuvers. The A* algorithm is guaranteed to find the shortest piecewise linear path to the goal position based on a uniformly decomposed map. Dynamic information is constructed and added to the A*-generated path, and provides an initial guess for warm starting the optimal control-based planner. The run time for the optimal control planner is greatly reduced by this initial guess and outputs a dynamically feasible and locally optimal trajectory.
关键词：KeywordsTrajectory planningenergy optimizationautonomous surface vehiclesoptimal control