Abstract
This paper proposes the use of a Voronoi-based heuristic to significantly speed up search-based nonholonomic path planning. Using generalized Voronoi diagrams (GVD) and in this manner exploiting geometric information about the obstacles, the presented approach is able to considerably reduce computation time while satisfying differential constraints using motion primitives for exploration. A key advantage compared to the common use of Euclidean heuristics is the inherent ability to avoid local minima of the cost function, which can be caused by, e.g., concave obstacles. Therefore, the application of the Voronoi-based heuristic is particularly beneficial in densely cluttered environments.
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Wang, Q., Wulfmeier, M., Wagner, B. (2016). Voronoi-Based Heuristic for Nonholonomic Search-Based Path Planning. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_33
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DOI: https://doi.org/10.1007/978-3-319-08338-4_33
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