Abstract
Aiming at the multiple Unmanned Aerial Vehicle (multi-UAV) task assignment problems, a multi-UAV task assignment algorithm based on the improved discrete pigeon-inspired optimization (PIO) algorithm is proposed considering various fitness functions and constraints. And a correction algorithm is designed for the constraint overflow problem in the algorithm. First, a multi-UAV task fitness function problem model is established with various benefits, costs, and constraints. In addition, referring to the idea of the learning factor in the particle swarm optimization (PSO) algorithm, the PIO algorithm is improved to strengthen the learning ability of the pigeons for global and local optimal information. Then, the improved PIO algorithm is discretized to fit the discrete task assignment model. Finally, aiming at the constraint overflow problem, a constraint check correction algorithm is designed to correct the constraint overflow sequence. Simulation experiments show that the improved discrete PIO algorithm can effectively solve the multi-UAV task assignment problem.
Fund program: The Fundamental Research Funds for the Central Universities (No. NS2021061). Fund Project of Key Laboratory of Complex System Control and Intelligent Collaboration Technology (202005).
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Wei, Y., Yang, B., Du, Y., Shen, H., Li, Y., Liu, Y. (2023). Multi-UAV Task Assignment Based on the Improved Discrete Pigeon-Inspired Optimization 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_708
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DOI: https://doi.org/10.1007/978-981-19-6613-2_708
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