Algorithms analysis of mobile robot SLAM based on Kalman and particle filter

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	Algorithms analysis of mobile robot SLAM based on Kalman and particle filter
	Zhang, Feng 2; Zhao, Languang 2; Sun, Enze 2; Yuan S(袁帅)1,2; Li, Siqi 2
	2017
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
关键词	mobile robot Simultaneous Localization and Mapping EKF-SLAM UKF-SLAM FastSLAM UFastSLAM
页码	1050-1055
通讯作者	Li, Siqi
中文摘要	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.
收录类别	EI
产权排序	2
会议录	Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-5090-6573-8
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/22415]
专题	沈阳自动化研究所_空间自动化技术研究室
作者单位	1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Information and Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, China
推荐引用方式 GB/T 7714	Zhang, Feng,Zhao, Languang,Sun, Enze,et al. Algorithms analysis of mobile robot SLAM based on Kalman and particle filter[C]. 见:9th International Conference on Modelling, Identification and Control, ICMIC 2017. Kunming, China. July 10-12, 2017.