To enhance the accuracy of path tracking and control for aircraft in three-dimensional space, this paper proposes a path planning method that integrates B-spline curves with a hybrid bald eagle optimization algorithm (HBEO). First, using flight distance, altitude, and smoothness as multi-dimensional optimization objectives, a parametric path model based on B-spline curves is constructed, achieving precise path description through the adjustment of control points. Second, to address the imbalance between global search and local exploitation in traditional intelligent algorithms, the HBEO is designed by deeply integrating the bionic hunting mechanism of the bald eagle optimization algorithm (BEO) with the spiral search strategy of the whale optimization algorithm (WOA), enhancing optimization capability in complex spaces by dynamically adjusting the search mode. Validation on the CEC2019 test suite shows that HBEO demonstrates higher convergence accuracy and late-stage search efficiency in multi-peak, high-dimensional function optimization. Finally, simulation experiments conducted in three-dimensional scenarios with complex obstacles indicate that, compared to BEO, WOA, PSO, and other algorithms, the paths generated by HBEO reduce total flight costs by 15%-30%, showing significantly better performance in key metrics such as distance, altitude, and smoothness.