Experimental Validation of Sensitivity-Aware Trajectory Planning for a Quadrotor UAV Under Parametric Uncertainty

In this work, we provide an experimental validation of the recent concepts of closed-loop state and input sensitivity in the context of robust flight control for a quadrotor (UAV) equipped with the popular PX4(1) controller. Our objective is to experimentally assess how the optimization of the reference trajectory w.r.t. these sensitivity metrics can improve the closedloop system performance against model uncertainties commonly affecting the quadrotor systems. To accomplish this, we present a series of experiments designed to validate our optimization approach on two distinct trajectories, with the primary aim of assessing its precision in guiding the quadrotor through the center of a window at relatively high speeds. This approach provides some interesting insights for increasing the closedloop robustness of the robot state and inputs against physical parametric uncertainties that may degrade the system's performance.