Abstract
This paper deals with the estimation of the localization of mobile robots based on robust Kalman filter. The data provided by odometric and sonar sensors are fused together using a robust filter to provide robot position and orientation estimates at each sampling time. Simulation results are presented, with a comparative study between the robust Kalman filter and the standard extended Kalman filter.
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