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Sonar and Video Data Fusion for Robot Localization and Environment Feature Estimation
By: Longhi, S.; La Manna, A.; Ippoliti, G.; Bonci, A.; Sartini, L.;
2005 / IEEE / 0-7803-9567-0
This item was taken from the IEEE Conference ' Sonar and Video Data Fusion for Robot Localization and Environment Feature Estimation ' In this paper the localization and environment feature estimation problems are formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, video camera and sonar measures. The environment is supposed to be only partially known, and a probabilistic method for sensory data fusion aimed at increasing the environment knowledge is considered.