Prioritizing Fuzzy Behaviors in Multi-robot Pursuit Teams

Abstract

The combination of fuzzy control and behavior hierarchies allows for the construction of more complex behavior-based robot control agents than does either technique alone. However, current implementations are limited in their complexity since high-level behaviors still use low-level sensor information. We propose a technique for abstracting this low-level sensor information into priorities which are used to completely abstract out the context in which a high-level, fuzzy behavior operates. This modification enables a single high-level behavior to coordinate the lower-level behaviors within a single robot, among the robots in a team, or even among teams of teams. This is demonstrated in a scenario in which multiple pursuers attempt to capture a prey.