Language-measure-based supervisory control of a mobile robot

This paper presents the design, modelling, and supervisory control of a mobile robot based on a signed real measure of its automaton (i.e., discrete-event behavior) language. While the robot's dynamic behavior is manipulated in the continuous-time domain via motion control and visual servoing, the mission planning is performed in the discrete-event supervisory control setting. However, unlike the conventional qualitative framework of supervisory control following the Ramadge-Wonham approach that is based on a set of specified constraints, a quantitative approach has been adopted for synthesis of optimal supervisory controllers in robotic scenarios with a language measure being the performance index. The parameters of the language measure are identified via both experimental observations and simulation runs; the results are consistent with each other as well as with other measures. This approach complements the Q-learning method that has been widely used in robotics research to learn primitive behaviors.