Abstract
Flight path planning is one of the key research issues in the field of unmanned aerial vehicles (UAVs). There have been various approaches proposed to find or plan an optimal or appropriate path for numerous UAV applications. The obtained paths will be followed as a navigation once the UAV flies. Related works have utilized different methods to find the paths for different situations or considerations in the flight environments. Several bio-inspired algorithms such as PSO, GA, ABC, and ACO as well as the graph-based A* algorithm were usually utilized in the solutions of path planning. In this paper, the concept of Floyd-Warshall algorithm and a grid-based map presenting environmental information are utilized to find an optimal path with minimum hop count. A simulator is also developed for this work. Several simulation results with different grid sizes are illustrated. This study presents a preliminary trial work of grid-based multi-hop route planning for UAVs. Both the grid model and concerned environmental information can be extended for further complex researches.
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Acknowledgement
This work is supported by the Fujian Provincial Natural Science Foundation in China (Project Number: 2017J01730) and the Education Department of Fujian Province (Project Number: GY-Z19005).
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Sung, TW., Sun, L., Chang, KC. (2020). Multi-hop Route Planning Based on Environment Information for Path-Following UAVs. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-44289-7_78
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DOI: https://doi.org/10.1007/978-3-030-44289-7_78
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