R-SLAM: Resilient localization and mapping in challenging environments

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• 作者：Muhammet Balcılar ^{muhammet@ce.yildiz.edu.tr}Author Vitae ; Sırma Yavuz ; ^{sirmax@ce.yildiz.edu.tr} ; Author Vitae ; Mehmet Fatih Amasyalı ^{mfatih@ce.yildiz.edu.tr}Author Vitae ; Erkan Uslu ^{erkan@ce.yildiz.edu.tr}Author Vitae ; Furkan Ç ; akmak ^{furkan@ce.yildiz.edu.tr}Author Vitae
• 关键词：SLAM ; Odometry error ; Pose correction ; Particle filter
• 刊名：Robotics and Autonomous Systems
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：87
• 期：Complete
• 页码：66-80
• 全文大小：3981 K
• 卷排序：87

文摘

A new particle filter based methodology called R-SLAM is proposed as a solution to simultaneous localization and mapping (SLAM) problem. R-SLAM introduces an improvement at the front-end, which makes this directly available during exploration. One of the strongest points of the R-SLAM is being able to produce accurate and high resolution maps. The data collected in historical Hagia Sophia Museum during this study is served to the research community.