Research on Multi-UAV Track Planning by Improving Grey Wolf Fusion Cuckoo Algorithm
Hengyi Huang · 2024
In this paper, an improved gray Wolf algorithm is proposed to solve the problem of multi-UAV cooperative path planning in multi-peak environment. Based on the original GWO algorithm, this paper innovatively introduces a dynamic weight adjustment mechanism to strengthen the global search capability, improve the local search accuracy, and effectively avoid the risk of premature convergence to the local optimal solution. The paper proposes to improve the integration strategy of gray Wolf algorithm and Cuckoo algorithm, and dynamically adjust the contribution proportion of the two algorithms. The performance of the algorithm is optimized and balanced. Through a series of standardized test functions and real scenario cases of multi-UAV flight path planning, the experimental results strongly show that the fusion algorithm proposed in this paper provides a more efficient, accurate and reliable optimization solution in the field of multi-UAV flight path planning, which has far-reaching academic contributions and broad practical application prospects.