Expert system framework for fault detection and fault tolerance in robotics

@inproceedings{Visinsky1994ExpertSF,
  title={Expert system framework for fault detection and fault tolerance in robotics},
  author={Monica L. Visinsky and Joseph R. Cavallaro and Ian D. Walker},
  year={1994}
}
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References

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A layered intelligent control framework is developed containing new sensor-based fault detection and tolerance schemes which provide different levels of detection andolerance probabilities for structurally diverse robots.
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This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot.
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The reachable measurement intervals method of computing dynamic thresholds is analyzed and its applicability to robotic fault detection is explored.
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The proposed fault diagnosis method needs only measurements from sensors which are necessary for robot control purposes, therefore no additional sensors ae required and practical issues concerning implementation and application are discussed.
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A framework for integrat- ing real-time software modules that comprise a reconfigurable multi-sensor based system based on the concept of a global database of state information through which real- time software modules exchange information is developed.
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The development necessary to allow a specific automation technology to be used effectively in DOE manufacturing operations is described and Sandia's research and development efforts on automated planning and programming, and on programming models and languages for “intelligent” manufacturing systems that use robots are described.
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An analysis of an improved joint drive system for the shuttle remote manipulator system (SRMS), capable of sustaining a single actuator failure, is presented and a feedback system that improves overall response is discussed.
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