Expert  System  Framework  for  Fault
         Detection  and  Fault  Tolerance  in  Robotics


         M. L. Visinsky, J. R. Cavallaro and I. D. Walker

       Department of Electrical and Computer Engineering
             Rice University, Houston, Texas 77251-1892



                             Abstract

          Fault tolerance is of increasing importance for
      modern robots. The ability to detect and tolerate
      failures enables robots to effectively cope with internal
      failures and continue performing assigned tasks without
      the need for immediate human intervention. To monitor
      fault tolerance actions performed by lower level routines
      and to provide higher level information about a robot's
      recovery capabilities, we present an expert system and
      critic which together form a novel and intelligent fault
      tolerance framework integrating fault detection and
      tolerance routines with dynamic fault tree analysis.
          A higher level, operating system inspired critic layer
      provides a buffer between robot fault tolerant operations
      and the user. The expert system gives the framework
      the modularity and flexibility to quickly convert between
      a variety of robot structures and tasks. It also provides
      a standard interface to the fault detection and tolerance
      software and a more intelligent means of monitoring the
      progress of failure and recovery throughout the robot
      system. The expert system further allows for
      prioritization of tasks so that recovery can take
      precedence over less pressing goals. Fault trees are used
      as a standard database to reveal the components
      essential to fault detection and tolerance within a
      system and detail the interconnection between failures in
      the system. The trees are also used quantitatively to
      provide a dynamic estimate of the probability of failure
      of the entire system or various subsystems.