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 effec tively detect and tolerate internal failures in order to continue perf orming 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 contin uous robot system and its normal controller, The interface layer monit ors the servo layer for sensor or motor failures using analytical redu ndancy based fault detection tests. A newly developed algorithm genera tes the dynamic thresholds necessary to adapt the detection tests to t he 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 sear ches for remaining tolerance options and initiates the appropriate act ion based on the current robot structure indicated by the fault tree d atabase, The layers form a hierarchy of fault tolerance which provide different levels of detection and tolerance capabilities for structura lly diverse robots.