Abstract
In this paper, an enhanced Artificial Potential Field (AFP) algorithm applied to autonomous mobile robot is presented. The proposed solution is extended by an additional BUG algorithm and a ground quality indicator. The modification allows to avoid local minima in path planning caused by complex terrain obstacles. The developed algorithm takes into account the substrate quality, classifying a poor ground as an obstacle. It was implemented and tested in Matlab software, utilizing the track planning algorithm as a state machine. The simulation environment enables graphical presentation of the chosen path and the arrangement of moving area. The article presents and discusses a basic issue in local path planning of autonomous mobile platforms, i.e. the ground quality, which is ignored in classical algorithms. This is a non-trivial problem, which impacts the success rate of getting the final destination. The developed algorithm is extended by a BUG rule and ground quality indicator which allows to avoid immobilization of the platform.
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Wyrąbkiewicz, K., Tarczewski, T., Niewiara, Ł. (2020). Local Path Planning for Autonomous Mobile Robot Based on APF-BUG Algorithm with Ground Quality Indicator. In: Bartoszewicz, A., Kabziński, J., Kacprzyk, J. (eds) Advanced, Contemporary Control. Advances in Intelligent Systems and Computing, vol 1196. Springer, Cham. https://doi.org/10.1007/978-3-030-50936-1_82
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DOI: https://doi.org/10.1007/978-3-030-50936-1_82
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