Credibilist Simultaneous Localization and Mapping with a LIDAR

被引：0
作者：
Trehard, Guillaume
Alsayed, Zayed
Pollard, Evangeline
Bradai, Benazouz
Nashashibi, Fawzi
机构：
来源：
2014 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2014) | 2014年
关键词：
MOBILE ROBOTS; SLAM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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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收藏
页码：2699 / 2706
页数：8
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