S. I., Sukhatme G.S., and Bekey G.A.:
Fault Detection and Identification in a Mobile Robot "
Multiple model adaptive estimation
(MMAE) is used to detect and identify sensor failures in a mobile robot. Each
estimator is a Kalman filter with a specific embedded failure model. The filter
bank also contains one filter which has the nominal model embedded within it.
The filter residuals are postprocessed to produce a probabilistic interpretation
of the operation of the system. The output of the system at any given time is
the confidence in the correctness of the various embedded models. As an additional
feature the standard assumption that the measurements are available at a constant,
common frequency, is relaxed. Measurements are assumed to be asynchronous and
of varying frequency. The particularly difficult case of 'soft' sensor failure
is also handled successfully. A system architecture is presented for the general
problem of failure detection and identification in mobile robots. As an example,
the MMAE algorithm is demonstrated on a Pioneer I robot in the case of three different