Disturbed behavior in co-operating autonomous robot

Balancing the conflicting demands imposed by a dynamic world on an autonomous robot requires a significant degree of adaptability. This paper describes a multi-layer control system for two co-operating mobile robots, which uses fuzzy logic to adapt the relative importance of a set of reactive behaviours. The fuzzy system therefore acts as an arbiter, which smoothly interpolates control between conflicting behaviours. This allows the robots to successfully navigate out of local potential minima. The adaptive mechanism itself is also modified by an array of vectors generated from an on-line analysis of the activity of each fuzzy rule. From recent work on neural dynamics [Kelso, 171 the strategy is to consider the control system as a dynamic structure, and to achieve adaptivity through maintaining it in a disturbed or stressed phase condition. This is achieved by monitoring the matrix of fuzzy rules, and triggering a suppression of rules which are driving the system into a stable state. We propose that for an autonomous agent in an unstructured environment maintaining a state of dynamic instability within the control system increases the probability of the agent reaching its goal.