Stochastic cloning: a generalized framework for processing relative state measurements
- Creators
- Roumeliotis, Stergios I.
- Burdick, Joel W.
Abstract
Introduces a generalized framework, termed "stochastic cloning," for processing relative state measurements within a Kalman filter estimator. The main motivation and application for this methodology is the problem of fusing displacement measurements with position estimates for mobile robot localization. Previous approaches have ignored the developed interdependencies (cross-correlation terms) between state estimates of the same quantities at different time instants. By directly expressing relative state measurements in terms of previous and current state estimates, the effect of these crosscorrelation terms on the estimation process is analyzed and considered during updates. Simulation and experimental results validate this approach.
Additional Information
© 2002 IEEE. This work has been supported by a grant from the Jet Propulsion Laboratory. The authors would like to thank Sam Pfister and Kristo Kriechbaum for their help with the WLSM algorithm and the collection of the experimental data.Attached Files
Published - 01014801.pdf
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Additional details
- Eprint ID
- 96687
- Resolver ID
- CaltechAUTHORS:20190625-092837711
- JPL
- Created
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2019-06-25Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field