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Abstract

Accurate estimates of mobile robot location, if available, can be used to improve the performance of a vehicle dynamics control system. To this purpose, the data provided by odometric and sonar sensors are here fused together by means of an extended Kalman filter, providing robot position and orientation estimates at each sampling instant. To cope with the tracking of long trajectories, the performance of the filter is improved by introducing an on-line fuzzy-rule-based adaptation scheme. © 1999 Elsevier Science Ltd. All rights reserved.

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Jetto, L., Longhi, S., & Vitali, D. (1999). Localization of a wheeled mobile robot by sensor data fusion based on a fuzzy logic adapted Kalman filter. Control Engineering Practice, 7(6), 763–771. https://doi.org/10.1016/S0967-0661(99)00028-3

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