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- W2066087344 abstract "In this work the localization of a mobile robot in an unknown environment is faced. A new version of the Extended Kalman Filter (EKF) is presented. The proposed EKF uses both measurements provided by robot on board and out of board sensors in order to emphasize the qualities and overcome the defects of such sensors. Moreover assuming a polynomial model for the robot surrounding environment bounds, an online algorithm able to build a map of this environment is presented. The proposed algorithms are tested in a numerical way contrasting them with a classical Extended Kalman Filter based only on the out of board sensors and with a fusing algorithm related only on the on board sensors." @default.
- W2066087344 created "2016-06-24" @default.
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- W2066087344 date "2013-06-01" @default.
- W2066087344 modified "2023-09-27" @default.
- W2066087344 title "Sensor fusion and surrounding environment mapping for a mobile robot using a mixed extended Kalman filter" @default.
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- W2066087344 doi "https://doi.org/10.1109/icca.2013.6565004" @default.
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