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Algorithms analysis of mobile robot SLAM based on Kalman and particle filter
Zhang, Feng1; Li, Siqi1; Yuan S(袁帅)1,2; Sun, Enze1; Zhao, Languang1
作者部门机器人学研究室
会议名称9th International Conference on Modelling, Identification and Control, ICMIC 2017
会议日期July 10-12, 2017
会议地点Kunming, China
会议录名称Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
出版者IEEE
出版地New York
2017
页码1050-1055
收录类别EI
EI收录号20183105618015
产权排序2
ISBN号978-1-5090-6573-8
关键词mobile robot Simultaneous Localization and Mapping EKF-SLAM UKF-SLAM FastSLAM UFastSLAM
摘要Many algorithms of mobile robot SLAM (Simultaneous Localization and Mapping) have been researched at present, however, the SLAM algorithm of mobile robot based on probability is often used in the unknown environment. In this paper, two kinds of SLAM algorithms based on probability are analyzed and compared. One kind is the SLAM algorithm based on Kalman filter: extended Kalman filter SLAM (EKF-SLAM) and unscented Kalman filter SLAM algorithm (UKF-SLAM). Another kind is the SLAM algorithm based on Particle filter: FastSLAM and unscented FastSLAM (UFastSLAM) algorithm. The difference from the four algorithms of SLAM is illustrated in terms of principle and calculation accuracy. Finally, the simulation results show that the UFastSLAM algorithm is superior to other algorithms in robot path and landmark estimation.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/22354
专题机器人学研究室
通讯作者Li, Siqi
作者单位1.Information and Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
推荐引用方式
GB/T 7714
Zhang, Feng,Li, Siqi,Yuan S,et al. Algorithms analysis of mobile robot SLAM based on Kalman and particle filter[C]. New York:IEEE,2017:1050-1055.
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