Abstract
With the extensive applications of Unmanned Aerial Vehicle (UAV), traditional approaches such as Artificial Potential Field and A-star for UAV track planning are usually limited by their low efficiency and easy failure, especially in the three-dimensional complex environments with obstacles. Moreover, most of these works do not make careful considerations on the fine-grain smooth of track requird heavily by the realistic flight of UAV. Therefore, in this paper, we propose an improved Biogeography-Based Optimization (BBO) algorithm with Bats algorithm (BA), named BIBBO for UAV track planning, which allows a new generating method with continuous Bezier curve by using adaptive-step sampling of control points to smooth original track. The simulation results verify the effectiveness and robustness of the proposed algorithm with shorter and smoother 3-D tracks, compared with typical BBO and BA algorithms.
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Acknowledgments
The authors would like to express their high appreciations to the supports from the National Natural Science Foundation of China (61871426), the Basic Research Project of Shenzhen (JCYJ20170413110004682) and the Verification Platform of Multi-tier Coverage Communication Network for Oceans (LZC0020).
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Chong, J., Qi, X., Yang, Z. (2021). Bat-Inspired Biogeography-Based Optimization Algorithm for Smoothly UAV Track Planning Using Bezier Function. In: Wu, Q., Zhao, K., Ding, X. (eds) Wireless and Satellite Systems. WiSATS 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-030-69069-4_9
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DOI: https://doi.org/10.1007/978-3-030-69069-4_9
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