Abstract
This paper introduces a new algorithm for solving the discrete grid-based coverage path-planning (CPP) problem. This problem consists in finding a path that covers a given region completely. Our algorithm is based on an iterative deepening depth-first search. We introduce two branch-and-bound improvements (Loop detection and Admissible heuristic) to this algorithm. We evaluate the performance of our planner using four types of generated grids. The obtained results show that the proposed branch-and-bound algorithm solves the problem optimally and orders of magnitude faster than traditional optimal CPP planners.
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Acknowledgments
We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds de Recherche du Québec—Nature et Technologies (FRQNT). We would also like to thank Alexandre Blondin-Massé, Guillaume Gosset, and the anonymous authors for their useful advices.
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Champagne Gareau, J., Beaudry, É., Makarenkov, V. (2021). Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2021. IDEAL 2021. Lecture Notes in Computer Science(), vol 13113. Springer, Cham. https://doi.org/10.1007/978-3-030-91608-4_9
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DOI: https://doi.org/10.1007/978-3-030-91608-4_9
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