Abstract: To enhance the path planning capability of Unmanned Aerial Vehicle(UAV) in complex three-dimensional environments,generating safe,efficient,and feasible flight path,a multi-strategy improved white shark optimizer is proposed.A spiral search strategy is employed to address the balance between exploration and exploitation,improving search efficiency.The crisscross strategy is used to optimize solution distribution,improving global search ability while further enhancing solution accuracy.A Cauchy mutation strategy is introduced to expand the search space and enhance population diversity,preventing premature convergence to local optima.To validate the algorithm’s optimization capability and its feasibility in UAV path planning,benchmark tests are first conducted based on the CEC2022 test functions.Subsequently,a three-dimensional terrain environment and UAV flight constraints are modeled,and comparative simulations are performed against other algorithms.Experimental results demonstrate that the proposed algorithm achieves superior optimization performance,reducing the mean fitness value of optimal solutions by 40.35%~68.64% compared to other algorithms.This demonstrates its capability to plan safer and more efficient UAV path.

Key words: UAV, Path planning, White shark optimizer, Spiral search, Crisscross, Cauchy mutation