As an application of the theory of Discrete Event Supervisory (DES) control presented in Chapters 1 and 2, this chapter addresses the design of a robotic system interacting with a dynamically changing environment. The work, reported in this chapter, encompasses the disciplines of control theory, signal analysis, computer vision, and artificial intelligence. Several traditional important methods are first reviewed to substantiate the DES control approach in the design of a mobile robotic system. Design and modelling of the behavior-based mobile robotic system are presented in details. The plant automaton model G of the robotic system is identified by making use of the available sensors and actuators. Then, a DES controller is synthesized based on the data collected from experimental scenarios. Through these experiments, performance of the robotic DES control system is quantitatively evaluated in terms of the language measure μ for both the unsupervised and supervised robotic systems. It is shown that the language measure μ can indeed be used as a performance index in the design of optimal DES control policies for higher level mission planning for behavior-based mobile robotic systems.
All Science Journal Classification (ASJC) codes
- Computer Science(all)