A Lyapunov-stable, sensor-based model for real-time path-tracking among unknown obstacles

The article proposes a feedback control system for real-time navigation and obstacle avoidance that is made of two components: (i) a sensor-based, real-time model that generates and periodically updates the path on-line in order to avoid both known and unforeseen obstacles, and (ii) a feedback-control model that is capable of driving a unicycle vehicle along the collision free path. The system has some unique characteristics, among which it requires very few computational resources as a consequence of its extreme simplicity. In spite of this, it is formally demonstrated to be asymptotically stable, as well as computationally efficient to be implemented in real-world scenarios where obstacles are not known, and possibly move in the environment.