Filling the gap between low frequency measurements with their estimates
conference paper
The use of redundant sensors brings a rich diversity of information, nevertheless fusing different sensors that run at vastly different frequencies into a proper estimate is still a challenging sensor fusion problem. Instead of using the size-varying measurements and thereby the size-varying filters during each sampling period, we propose to find a substitute of the unavailable low frequency measurements such that we can avoid using different sampling frequencies in one filter. In the gap between the sampling of two low frequency measurements, the use of these substitutes produces smoother estimates. In both the proof of concept simulation and the localization experiment performed on an indoor soccer robot, our proposed approach exhibits an improved performance compared to the size-varying Kalman filter methods. cop. 2014 IEEE.
TNO Identifier
525557
ISSN
10504729
Publisher
Institute of Electrical and Electronics Engineers Inc.
Article nr.
6906606
Source title
Proceedings - IEEE International Conference on Robotics and Automation
Pages
175-180
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