EKF-SLAM Statistical Bounds Considering Intermittent Measurements
This paper presents a theoretical study of intermittent measurement in EKF-SLAM(Simultaneous Localization and Mapping) Problem. We propose the analysis of FIM(Fisher Information Matrix) to illustrate the uncertainties statistical bounds whenever measurement data is not arrived to the system. Th...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/3062/ http://umpir.ump.edu.my/3062/1/MUCET_final.pdf |
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| Summary: | This paper presents a theoretical study of intermittent
measurement in EKF-SLAM(Simultaneous Localization
and Mapping) Problem. We propose the analysis of FIM(Fisher
Information Matrix) to illustrate the uncertainties statistical
bounds whenever measurement data is not arrived to the
system. The FIM explains the behavior of information when
a measurement data is partially unavailable and therefore its
existence is important to describe the system performance. The
information obtained from the updated state error covariance
demonstrates that the resultant state error covariance never
exceeds this boundaries if a measurement data is missing during
mobile robot observations. Simulation under certain conditions
consistently assures the results is agreeing with the proposed
analysis.
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