Abstract
Motion planning is an important and well-studied field of robotics. A typical approach to finding a route is to construct a cell graph representing a scene and then to find a path in such a graph. In this paper we present and analyze parallel algorithms for constructing the cell graph on a SIMD-like GPU processor.
Additionally, we present a new implementation of the dictionary data type on a GPU device. In the contrary to hash tables, which are common in GPU algorithms, it uses a radix search tree in which all values are kept in leaves. With such a structure we can effectively perform dictionary operations on a set of long vectors over a limited alphabet.
The research was funded by National Science Center, decision DEC-2012/07/D/ST6/02483.
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Acknowledgement
The authors are sincerely grateful to Joanna Porter-Sobieraj and Przemysław Dobrowolski for introducing us to the problem and useful advice on possible applications in motion planning. We acknowledge the support of National Science Center, decision DEC-2012/07/D/ST6/02483.
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Kaczmarski, K., Rzążewski, P., Wolant, A. (2016). Massively Parallel Construction of the Cell Graph. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_52
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DOI: https://doi.org/10.1007/978-3-319-32149-3_52
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