Abstract
In this paper we present a motion planning algorithm that combines between Probabilistic Roadmaps (PRM) and Hierarchical Genetic Algorithms (HGA) in order to generate optimal motions for a non holonomic mobile robot. PRM are used to generate a set of paths that will be optimized by HGA, the obtained trajectory leads a non holonomic mobile robot from an initial to a final configuration while maintaining feasibility and no-collision with obstacles.
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Lakhdari, A., Achour, N. (2015). Probabilistic Roadmaps and Hierarchical Genetic Algorithms for Optimal Motion Planning. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems in Science and Information 2014. SAI 2014. Studies in Computational Intelligence, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-14654-6_20
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DOI: https://doi.org/10.1007/978-3-319-14654-6_20
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