We present improvements to a recently developed method for trajectory planning for autonomous surface vehicles (ASVs) in terms of run time. The original method combines two types of planners: An A* implementation that quickly finds the global shortest piecewise linear path on a uniformly discretized map, and an optimal control-based trajectory planner which takes into account ASV dynamics. Firstly, we propose an improvement to the discretization of the map by switching to a Voronoi diagram rather than the uniform discretization, which offers a far more sparse search tree for the A* implementation. Secondly, modifications to the path refinement are made, as suggested in a paper by Bhattacharya and Gavrilova. The changes result in a reduction to the run time of the first part of the method of 85% for an example scenario while maintaining the same level of optimality.
@article{arxiv.1908.07311,
title = {Improvements to Warm-Started Optimized Trajectory Planning for ASVs},
author = {Glenn Bitar and Anastasios M. Lekkas and Morten Breivik},
journal= {arXiv preprint arXiv:1908.07311},
year = {2019}
}
Comments
9 pages, 6 figures, 2 tables. Preprint as submitted to a special issue on Maritime Robotics and Control Systems of the International Journal of Control, Automation and Systems