Abstract
Path planning of an Unmanned Aerial Vehicle (UAV) is NP complete problem. It is a hard problem to solve, especially when the number of control points is high and the number of radar is more, even more so. At present, the intelligent algorithm becomes the mainstream method of UAV route planning problem. For this question, this paper proposed an improved hybrid cuckoo search algorithm, combined with the crossover and mutation operator of genetic algorithm. Simulation results show that when the number of control points is high and the number of radar is more, this method can offer a safe and effective path planning for unmanned aerial vehicle.
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Acknowledgment
This work is supported by the Project of Guangxi High School Science Foundation under Grant no. KY2015YB539
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Xie, C., Zheng, H. (2016). Application of Improved Cuckoo Search Algorithm to Path Planning Unmanned Aerial Vehicle. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_72
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DOI: https://doi.org/10.1007/978-3-319-42291-6_72
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