Supervisory control of multiple robots subject to context switching

Abstract

Coordinating concurrent multiple robots, in an efficient manner, is a task that challenges control engineers by its complexity. To be properly addressed, this task usually requires the support of formal approaches, such as the Supervisory Control Theory (SCT), which provides an automated way to calculate control strategies for event-based robots coordination. Little has been reported, however, on how to program controllers that automatically adapt themselves to the system context. In fact, self-adaptation support implies providing the robot brain with context-sensitive control strategies subject to changes at runtime. Without self-adaptation, on the other hand, each system configuration may require an entire control solution to be recalculated, which implies reestablishing the whole modeling structure. This paper shows that a system model can nevertheless be enriched with elements collected from the system context, which optimizes the design of formula-based constraints that can then be integrated to the SCT framework for control synthesis and posterior code generation. The result is a controller that recognizes the context and take control decisions accordingly. An example of multiple robots coordination illustrates the approach.