Fault Diagnosis and Fault-tolerant Control of Robotic and Autonomous Systems

Applications involving multi-robot systems have been increasing day by day, since they allow one to accomplish complex tasks otherwise impossible for a single unit. Common control approaches for these robot systems are based on distributed architecture, where each robot computes its own control input, only based on local information from onboard sensors or received from its neighbor robots. This means that the failure of one or more agents might jeopardize the task execution. For this reason, fault detection and isolation (FDI) strategies become crucial to accomplish the assigned task in the aforementioned case as well. This chapter presents a distributed fault diagnosis architecture aimed at detecting failures in a team of robots working in tight cooperation. The proposed approach relies on a distributed observer-controller scheme, where each robot estimates the overall system state by means of a local observer, and it uses such an estimate to compute the local control input to achieve a specific task. The local observer is also used to define a set of residual vectors aimed at detecting and isolating faults occurring on any robot of the team, even if there is no direct communication. The approach is validated through experiments where a heterogeneous team of three robots perform a cooperative task.