Collaborative mission planning algorithm for multiple UAVs based on virus marketing model
Authors: 
Guilan Luo, Xin Ma, Yuanbo Zhu, Anqi Cao, Xuan Liu, Shuailin WangAuthors Info & Claims
Guilan Luo, Xin Ma, Yuanbo Zhu, Anqi Cao, Xuan Liu, Shuailin WangAuthors Info & ClaimsPages 109 - 113
Abstract
Facing the problems of low efficiency, high complexity, and poor convergence in collaborative task planning for multiple UAVs in complex environments, this paper proposes a collaborative task planning algorithm for multiple UAVs based on virus propagation behavior and particle swarm optimization algorithm. This algorithm utilizes the propagation advantages of virus marketing models such as low cost, high efficiency, and exponential level. By adding virus particles, and it improves the optimization process of global and individual optimal particles, while combining the characteristics of inert particles to optimize the convergence process of ordinary particles. The robustness achieved 99% through experimental simulation, it is found that compared to the other three algorithms, the average task planning time of this algorithm is reduced by 21.30%, 28.57%, and 164.28%, respectively, and the robustness is reduced by 4%, 1%, and - 1%, respectively.
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January 2024
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Published: 08 March 2024
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CCEAI 2024
CCEAI 2024: 2024 8th International Conference on Control Engineering and Artificial Intelligence
January 26 - 28, 2024
Shanghai, China
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