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The Application of Square-root Cubature Kalman Filter in SLAM for Underwater Robot
Li X(李勋); Feng YB(冯迎宾); Huang RH(黄荣辉); Zhang X(仉新); Liu SG(刘顺贵); Ai JW(艾静文)
作者部门水下机器人研究室
会议名称2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
会议日期October 20-22, 2017
会议地点Jinan, China
会议录名称2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
出版者IEEE
出版地New York
2017
页码2183-2187
收录类别EI ; CPCI(ISTP)
EI收录号20183005604752
WOS记录号WOS:000427816102049
产权排序2
ISBN号978-1-5386-3524-7
关键词Simultaneous Localization And Mapping(Slam) Square Root Cubature Kalman Filter Jacobian Matrix Underwater Robots
摘要

For simultaneous localization and mapping(SLAM) of underwater robots, the extended kalman filter algorithm has the problems of slow convergence rate, low accuracy and poor numerical stability, and square root cubature Kalman filter SLAM algorithm (SRCKF-SLAM) for mobile robots is designed according to cubature Kalman filter (CKF) principle. The cubature rule is utilized to calculate Gaussian weighted integral of the nonlinear function and robot pose particle’s weight. The square root of the covariance is usedto replace the system covariance matrix, which reduces the influence of truncation error on precision of SLAM. Simulation results show that the SRCKF algorithm has the advantages of high estimation accuracy, fast speed and stable convergence, which verify the effectiveness of the algorithm.

语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21292
专题水下机器人研究室
通讯作者Li X(李勋)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang Liaoning 110870, China
2.School of Mechanical Engineering, Shenyang University of Technology, Shenyang, Liaoning 110870, China
推荐引用方式
GB/T 7714
Li X,Feng YB,Huang RH,et al. The Application of Square-root Cubature Kalman Filter in SLAM for Underwater Robot[C]. New York:IEEE,2017:2183-2187.
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