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A FastSLAM algorithm based on the Unscented Filtering with adaptive selective resampling

Abstract : A FastSLAM approach to the SLAM problem is considered in this paper. An improvement to the classical FastSLAM algorithm has been obtained by replacing the Extended Kalman Filters used in the prediction step and in the feature update with Unscented Kalman Filters and by introducing an adaptive selective resampling. The simulations confirm the effectiveness of the proposed modifications.
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https://hal.inria.fr/inria-00258750
Contributor : Fabio Martinelli <>
Submitted on : Monday, February 25, 2008 - 11:12:31 AM
Last modification on : Monday, February 25, 2008 - 7:09:19 PM
Long-term archiving on: : Friday, September 28, 2012 - 10:10:17 AM

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  • HAL Id : inria-00258750, version 1

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Manuel Cugliari, Francesco Martinelli. A FastSLAM algorithm based on the Unscented Filtering with adaptive selective resampling. 6th International Conference on Field and Service Robotics - FSR 2007, Jul 2007, Chamonix, France. ⟨inria-00258750⟩

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