A Dynamic Fault Tolerance Framework for Remote Robots

Fault tolerance is increasingly important for robots, especially those in remote or hazardous environments. Robots need the ability to effectively detect and tolerate internal failures in order to continue performing their tasks without the need for immediate human intervention. This paper presents a layered fault tolerance framework containing new fault detection and tolerance schemes. The framework is divided into servo, interface, and supervisor layers. The servo layer is the continuous robot system and its normal controller. The interface layer monitors the servo layer for sensor or motor failures using analytical redundancy based fault detection tests. A newly developed algorithm generates the dynamic thresholds necessary to adapt the detection tests to the modeling inaccuracies present in robotic control. Depending on the initial conditions, the interface layer can provide some sensor fault tolerance automatically without direction from the supervisor. If the interface runs out of alternatives, the discrete event supervisor searches for remaining tolerance options and initiates the appropriate action based on the current robot structure indicated by the fault tree database. The layers form a hierarchy of fault tolerance which provide different levels of detection and tolerance capabilities for structurally diverse robots