Robust image-based control for aerial interaction under external disturbances

This paper proposes a robust image-based control framework for an aerial manipulator (AM) performing infrastructure contact inspection under strong coupling, uncertainties, and external disturbances. A decoupled second-order image dynamics model is derived from virtual-camera image moments. Building on this model, a disturbance observer-based nonlinear model predictive controller (NMPC) is developed to generate position commands, where disturbances are estimated online, and both physical limits and visibility constraints are explicitly enforced. To achieve reliable force interaction, an image-based first-order variable-stiffness impedance controller is designed for contact-direction force-tracking, and a geometric attitude controller based on a commanded filter is adopted to avoid Euler angle singularities. Simulation and experimental results demonstrate improved tracking accuracy and robustness. The contact force RMSE is reduced by 31.6% compared with a representative robust NMPC baseline in simulation, and by 58.3% compared with a hybrid visual compliant baseline in experiments, across nine repeated trials; the average force RMSE reduction reaches 52.9%. These results verify the force-tracking accuracy and reproducibility of the proposed framework in aerial physical interaction (APhI) tasks.