Hierarchical model-based diagnosis for high autonomy systems

Deep reasoning diagnostic procedures are model-based, inferring single or multiple faults from the knowledge of faulty behavior of component models and their causal structure. The overall goal of this paper is to develop a hierarchical diagnostic system that exploit knowledge of structure and behavior. To do this, we use a hierarchical architecture including local and global diagnosers. Such a diagnostic system for high autonomy systems has been implemented and tested on several examples in the domain of robot-managed fluid-handling laboratory.

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