Trajectory Optimization of Aircraft Based on Intelligent Bionic Algorithm

With the continuous advancement of AI intelligent algorithms, significant progress has been achieved in unmanned systems research. Among these, the intelligent selection of autonomous flight paths for unmanned aerial vehicles (UAVs) holds substantial research value. The application of bio-inspired intelligent algorithms to solve the optimal flight trajectory for UAVs is critically important. This study first establishes a spline interpolation model for UAV flight trajectories, deriving the mathematical expression of the trajectory based on multiple key points. Subsequently, a wolf pack optimization algorithm is developed to simulate and compute the optimal flight trajectory among infinite possible paths. Finally, comprehensive validation is conducted on the MATLAB simulation platform. Simulations under various initial conditions and scenarios with randomly generated obstacles demonstrate the ability to solve for the optimal flight path accurately. The results rigorously confirm the correctness of the algorithm's application and provide effective guidance for subsequent UAV flight path design.