Mitchell Torok, Man Ching Melvin Chan, Donglin Sui, Mohammad Deghat
Quadrotors performing sensing missions near structures such as turbines, towers, and buildings must hold a stable attitude while traversing the structured wind wakes generated by these structures. To maintain trajectory tracking in wind, the vehicle must tilt continuously, and the inner-loop controller must work harder to hold that tilt against the fluctuating flow, raising mean tilt, angular jerk, and command-rate activity. These attitude-domain costs can degrade onboard imagery and gimbal-stabilized sensor data, consuming the actuator authority required to reject further disturbances. Existing work typically treats the two halves of this problem separately: wind is either estimated locally and compensated reactively, or routed around in fields assumed known a priori, and is rarely validated against attitude-domain metrics on hardware. These approaches are most effective when coupled through a single shared representation. A nonlinear disturbance observer estimates wind from the vehicle's translational dynamics and accumulates it into a spatial map, which simultaneously provides per-stage feedforward compensation to a contouring controller and weights a wind-aware A* planner. On hardware, the estimator matches anemometer ground truth to within 1m/s, and a 2×2 ablation study across three wind configurations shows a reduction of up to 38% in tilt RMS and 28% in its 95th percentile relative to a wind-naive baseline, at the cost of longer paths.