System identification and control of the ground operationmode of a hybrid aerial–ground robot

This paper presents an in-depth analytical and empirical assessment of the performance of DoubleBee, a novel hybrid aerial–ground robot. Particularly, the dynamic model of the robot with ground contact is analyzed, and the unknown parameters inthe model are identified. We apply an unscented Kalman filter-based approach and a least square-based approach to estimatethe parameters with given measurements and inputs at every time step. Real data are collected and used to estimate theparameters; test data verify that the values obtained are able to model the rotation of the robot accurately. A gain-scheduledfeedback controller is proposed, which leverages the identified model to generate accurate control inputs to drive the systemto the desired states. The system is proven to track a constant-velocity reference signal with bounded error. Simulations andreal-world experiments using the proposed controller show improved performance than the PID-based controller in trackingstep commands and maintaining attitude under robot movement.