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. ; publishedVersion ; © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. Under a Creative Commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Warm-Started Optimized Trajectory Planning for ASVs
2019-01-01
cristin:1794657
308-314 ; 52 ; IFAC-PapersOnLine ; 21
Article (Journal)
Electronic Resource
English
DDC: | 629 |
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