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Credibilist Simultaneous Localization and Mapping with a LIDAR

Abstract : From the early beginning, the Simultaneous Localization And Mapping (SLAM) problem has been approached using a probabilistic background. A new solution based on the Transferable Belief Model (TBM) framework is proposed in this article. It appears that this representation of knowledge affords numerous advantages over the classic probabilistic ones and leads to particularly good performances (an average of 3.2% translation drift and 0.0040deg/m rotation drift), especially when it comes to crowded environment. By introducing the basic concepts of a Credibilist SLAM, this article aims at proving that the use of this new theoretical context opens a lot of perspectives for the SLAM community.
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Contributor : Guillaume Trehard Connect in order to contact the contributor
Submitted on : Wednesday, September 24, 2014 - 12:46:48 PM
Last modification on : Friday, January 21, 2022 - 3:14:11 AM
Long-term archiving on: : Friday, April 14, 2017 - 2:13:02 PM


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  • HAL Id : hal-01067931, version 1



Guillaume Trehard, Zayed Alsayed, Evangeline Pollard, Benazouz Bradai, Fawzi Nashashibi. Credibilist Simultaneous Localization and Mapping with a LIDAR. IROS - International Conference on Intelligent Robots and Systems, Sep 2014, Chicago, United States. ⟨hal-01067931⟩



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