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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)
Department水下机器人研究室
Conference Name2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
Conference DateOctober 20-22, 2017
Conference PlaceJinan, China
Source Publication2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
PublisherIEEE
Publication PlaceNew York
2017
Pages2183-2187
Indexed ByEI ; CPCI(ISTP)
EI Accession number20183005604752
WOS IDWOS:000427816102049
Contribution Rank2
ISBN978-1-5386-3524-7
KeywordSimultaneous Localization And Mapping(Slam) Square Root Cubature Kalman Filter Jacobian Matrix Underwater Robots
Abstract

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.

Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21292
Collection水下机器人研究室
Corresponding AuthorLi X(李勋)
Affiliation1.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
Recommended Citation
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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