Distributed diagnosis of coupled mobile robots

Fault diagnosis of coupled mobile robots requires a large number of measurements to be communicated either between the robots or from the robots to a central diagnoser. As computational complexity increases with the number of measurements, centralized algorithms become inefficient. This paper presents a distributed approach for qualitative fault diagnosis of coupled mobile robots. The approach is based on a bond graph modeling framework which incorporates local and distributed control algorithms, multiple sensor types, and both actuator and sensor faults. Relative measurement orderings are introduced to discriminate faults by exploiting the temporal order of the measurement deviations. This increases the discriminatory power or a set of measurements and results in a more efficient qualitative diagnosis algorithm. Distributed diagnosers are designed and applied to coupled mobile robots. Experimental results for a system consisting of two robots pushing a box demonstrate the improvement in both discriminatory power of the measurements and efficiency of the distributed diagnosis approach.