An Information-aware Lyapunov-based MPC for autonomous robots

This paper proposes a feedback-feedforward control scheme that combines the benefits of an online active sensing control strategy to maximize the information needed for correctly executing the desired task (the feedforward component), with a Lyapunov-based control strategy that guarantees an asymptotic convergence towards the task itself (the feedback component). To show the effectiveness of our method, we consider a unicycle equipped with onboard sensors that has to perform the classical path following task.