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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
Description
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.
Related Topics
Sonar Measurements
Uncertainty
Filtering
Robot Vision Systems
Cameras
Stochastic Processes
Vehicles
Mobile Robots
Robot Localization
Engineering
Simultaneous Localization And Mapping
