A  Dynamic  Fault  Tolerance  Framework  for Remote  Robots


       Monica L. Visinsky, Joseph R. Cavallaro and Ian D. Walker

            Department of Electrical & Computer Engineering
               Rice University Houston, TX 77251-1892


                              Abstract

          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.