A Hybrid-State Path Planner for ASV Formations with Full-Scale Experiments
Else-Line M. Ruud, Marius S. Rundhovde, Jarle Sandrib, Glenn Bitar
Abstract
We present a hybrid-state path planner for autonomous surface vehicles (ASVs) constrained by a min-imum turning radius. The work is motivated by the future Norwegian naval mine countermeasures (NMCM) concept, which includes mine sweeping operations with ASVs that operate alone or in a formation of two, with and without mine sweeping equipment attached. Our path-planning approach is a variant of hybrid A* search, with the goal of finding the shortest path for transit in an environment consisting of an a priori map, operator-defined avoid areas and static obstacles detected by the vehicle. The planner is capable of finding traversable paths for ASV formations and single vehicles using a simple geometric model based on an estimated minimum turning radius for a given configuration. The method is modular as it is uncoupled from the path-following control method, making it applicable to many different systems, including our ASV configurations for mine sweeping operations. We present results from path planning in simulation for a single vehicle and two vehicles in formation. The method has been validated through a full-scale experiment with one of our ASVs in our testing area for autonomous platforms.
BibTeX
@inproceedings{iros2023_ahybridstatepath,
title = {A Hybrid-State Path Planner for ASV Formations with Full-Scale Experiments},
author = {Else-Line M. Ruud and Marius S. Rundhovde and Jarle Sandrib and Glenn Bitar},
booktitle = {IROS 2023},
year = {2023}
}