文章基本信息

标题：An Optimization-Based Receding Horizon Trajectory Planning Algorithm
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作者：Kristoffer Bergman ; Oskar Ljungqvist ; Torkel Glad 等
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：15550-15557
DOI：10.1016/j.ifacol.2020.12.2399
语种：English
出版社：Elsevier
摘要：AbstractThis paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. The proposed approach is a two-step procedure that uses a motion planning algorithm in a first step to efficiently find a feasible, but possibly suboptimal, nominal solution to the trajectory planning problem where in particular the combinatorial aspects of the problem are solved. The resulting nominal trajectory is then improved in a second optimization-based receding horizon planning step which performs local trajectory refinement over a sliding time window. In the second step, the nominal trajectory is used in a novel way to both represent a terminal manifold and obtain an upper bound on the cost-to-go online. This enables the possibility to provide theoretical guarantees in terms of recursive feasibility, objective function value, and convergence to the desired terminal state. The established theoretical guarantees and the performance of the proposed algorithm are verified in a set of challenging trajectory planning scenarios for a truck and trailer system.
关键词：KeywordsTrajectoryPath PlanningOptimal ControlAutonomous Vehicles