To address the requirements of safe obstacle avoidance and path efficiency for 3D unmanned aerial vehicle (UAV) path planning in complex environments

a 3D UAV path planning method based on a multi-strategy improved black-winged kite algorithm

FBKA，is proposed. Firstly

a shared hunting ground strategy is incorporated

and a dimension-adaptive Poisson distribution is introduced to enhance the algorithm’s global search efficiency and convergence speed

thereby laying the foundation for rapidly identifying the optimal path direction of path planning.Secondly

a reconnaissance-and-encirclement strategy is introduced to strengthen the algorithm’s obstacle avoidance capability and robustness in escaping local optima

preventing collisions or redundant detours during path planning. Finally

an adaptive migration strategy is added to maintain search space diversity in the later iterations of the algorithm

optimizing the rationality of path altitude and global optimality

while avoiding excessive path altitude fluctuations. Experimental results demonstrate that FBKA presents superior optimization performance

stability

and comprehensive performance in 3D UAV path planning compared with other advanced algorithms proposed in recent years.