This paper proposes a novel solution to the trajectory tracking control problem for input-constrained differentialdrive robots. In particular, we develop a robust set-based receding horizon tracking scheme capable of dealing with state-dependent input constraints arising when the vehicle’s dynamics are approached by a standard feedback linearization technique. First, offline, we characterize the worst-case input constraint set and compute an admissible, although not optimal, controller. Then, online, we leverage the knowledge of the robot’s orientation to enlarge the constraint set in a receding-horizon fashion and, consequently, improve the tracking performance. Recursive feasibility and constraints fulfillment are formally proven. The approach’s effectiveness is experimentally validated on a Khepera IV differential-drive robot by comparing the control performance with several competitor schemes.

C. Tiriolo, G. Franze', W. Lucia, IEEE Transactions on Control Systems Technology (TCST), DOI 10.1109/TCST.2022.3219298, 2022