Dynamic Trajectory Planning for Autonomous Parafoil Homing Under Wind Disturbances

The parafoil is highly susceptible to deviations from its reference trajectory under wind disturbances. Given its constrained longitudinal control authority, it has limited capability to correct these deviations and regain the intended glide path. To overcome this limitation, we propose a dynamic planning framework based on a layered homing strategy. The airdrop mission trajectory is initially designed as a traditional multi-segment path. To approximate non-uniform glide characteristics under wind disturbances, this planning problem incorporates a predicted wind model as an external input. Node parameters of the segmented trajectory are then solved using an improved grey wolf optimizer (IGWO). By tracking this reference trajectory, the parafoil is guided into the proximity of the target. To ensure landing precision, the terminal phase is formulated and discretized using an adaptive pseudo-spectral method (APSM). The online planner computes a real-time trajectory to account for actual motion characteristics. This dynamic replanning (DRP) compensates for deviations caused by model mismatches and external disturbances. The proposed homing method is statistically verified via extensive Monte Carlo simulations under different wind conditions. Finally, the airdrop experiment is conducted to validate the DRP method.