The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Autonomous fault detection is prerequisite for autonomous system repair which is of great value for spacecraft where human intervention is expensive, slow, unreliable, and occasionally impossible. We present a method which successfully achieves autonomous fault detection in simulation. The approach uses a nonparametric estimate of the system state updated based upon sensor measurements. Our system does state estimation using a decision-theoretic generalization of particle filters which takes into account the difference in utility of fault detection vs. fault nondetection.

Keywords

Fault Identification, Particle Filters, Hybrid state estimation

Notes

Associated Center(s) / Consortia: Field Robotics Center

Associated Project(s): Sun Synchronous Navigation

Note: Supported in part by NASA Ames Summer Student Research Program 2000

Text Reference

Vandi Verma, John Langford, and Reid Simmons, "Non-Parametric Fault Identification for Space Rovers," International Symposium on Artificial Intelligence and Robotics in Space (iSAIRAS), June, 2001.

BibTeX Reference

@inproceedings{Verma_2001_3759,
   author = "Vandi Verma and John Langford and Reid Simmons",
   editor = "Jean-Claude Piedboeuf",
   title = "Non-Parametric Fault Identification for Space Rovers",
   booktitle = "International Symposium on Artificial Intelligence and Robotics in Space (iSAIRAS)",
   month = "June",
   year = "2001",
   Notes = "Supported in part by NASA Ames Summer Student Research Program 2000"
}

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