Abstract
To address the issue of multi-UAVs cooperative combat and realize threat avoidance in 3D space, a cooperative collision avoidance route planning strategy based on improved RRT algorithm is proposed. Firstly, the planning space establishment, constraint analysis and threat modeling are carried out. Aiming at the shortcoming of lacks of preference in searching while using RRT algorithm, a biased principle to improve the selection strategy was proposed, which leaded random number close to the target. Meanwhile, the improved algorithm is applied to the planning process of multi-UAVs cooperative route planning. Finally, the feasibility of cooperative collision avoidance route planning strategy based on improved RRT algorithm is verified by simulation analysis. By comparison, the improved algorithm can close to optimum with less time, which proves the effect of the algorithm.
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References
Liu, Y., Zhao, Y.: A virtual-waypoint based artificial potential field method for UAV path planning. In: Proceedings of the 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), pp.945–949. IEEE (2016)
Li, J.H., Liu, Q.F.: The research of unmanned aerial vehicles (UAV) dynamic path planning based on sparse A* algorithm and an evolutionary algorithm. J. Appl. Sci. 35(1), 128–138 (2017)
Aghababa, M.P., Amrollahi, M.H., Borjkhani, M.: Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles. J. Mar. Sci. Appl. 11(3), 378–386 (2012)
Du, M., Chen, J., Zhao, P.: On the RRT-based motionpliner for customised environs. In: Proceedings of the IEEE International Coherence on Robotics and Automation, pp.4674–4679. IEEE (2014)
David, B.: Comparison of A* and RRT-connect motion planning techniques for self-reconfiguration planning. In: Proceedings of the International Conference on Intelligent Robots and Systems, Beijing, pp. 892–897. IEEE/RSJ (2016)
Li, M.: Research on UAV Mission Planning Methods Based on Intelligent Optimization and RRT Algorithm. Nanjing University of Aeronautics & Astronautics, Nanjing (2012)
Kiesel, S., Burns, E., Ruml, W.: Abstraction-guided sampling for motion planning. University of New Hampshire Department of Computer Science Technical Report 12–01 (2012)
Sebastian, K., Jan, O.: RRT*-Connect: faster, asymptotically optimal motion planning. In: Proceedings of the IEEE Conference on Robotics and Biomimetics, pp. 1670–1677. IEEE (2015)
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Yike, S., Mingwei, L., Shaoqing, Z., Yanwei, W. (2023). Cooperative Collision Avoidance Route Planning Based on Improved RRT Algorithm. In: Yan, L., Duan, H., Deng, Y. (eds) Advances in Guidance, Navigation and Control. ICGNC 2022. Lecture Notes in Electrical Engineering, vol 845. Springer, Singapore. https://doi.org/10.1007/978-981-19-6613-2_17
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DOI: https://doi.org/10.1007/978-981-19-6613-2_17
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