Autonomous Tracked Vehicles Operating in Cluttered and Unknown Environments: A Networked Set-Theoretic Receding Horizon Control Strategy.

In this article, the constrained navigation problem for autonomous robots moving in unknown cluttered environments is considered. In particular, it is required to ensure the safety of the path planning and control units during the on-line operations. This statement gives rise to a networked control framework whose the key critical aspects are addressed by resorting to model predictive control technicalities developed within a set-theoretic approach. In particular, a novel control architecture is conceived whose the main features can be summarized as follows: anti-collision capabilities despite time-induced time-delay occurrences along the communication medium; mission accomplishment despite unpredictable obstacle occurrences along the nominal path. These properties are formally proven together with ultimate uniformly boundedness and constraints fulfillment of the regulated trajectory regardless of the vehicle uncertainties. In particular, SSTMR are considered for their flexibility and adaptability to operate in arduous scenarios for hazard missions. Final experiments are provided to show the effectiveness and to highlight the main advantages of the proposed control architecture.