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Bearings-only cooperative localization algorithm of multi-mobile robots based on square-root unscented Kalman filter


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Bearings-only cooperative localization algorithm of multi-mobile robots based on square-root unscented Kalman filter
Wang BixiaLi YinyaQi GuoqingSheng Andong
School of Automation,NUST,Nanjing 210094,China
cooperative localization multi-mobile robots bearings-only square-root unscented Kalman filter incomplete measurements computation complexity relative bearings self-localization
In order to solve the trade-offs between localization accuracy and real-time in the multi-mobile robots localization,a bearings-only cooperative localization algorithm of multi-mobile robots based on square-root unscented Kalman filter(SR-UKF)is presented.The dynamic model of the multi-mobile robots self-localization system is proposed according to the kinematics equation and the measurement equation.The method uses the relative bearings as measured values,and the square root of covariance matrix is delivered directly in the filtering to update the system state.The distributed self-localization is realized.The simulation results show that,under the same conditions,compared with the existing algorithms,the localization accuracy of the proposed SR-UKF algorithm is increased by nearly one time,and the single average execution time is reduced by 2/3.


[1] 谭民,王硕,曹志强.多机器人系统[M].北京:清华大学出版社,2005.
Tan Min,Wang Shuo,Cao Zhiqiang.Multi-robot systems[M].Beijing:Tsinghua University Press,2005.
[2]Maczka D K,Gadre A S,Stilwell D J.Implementation of a cooperative navigation algorithm on a platoon of autonomous underwater vehicles[A].IEEE International Conference on OCEANS[C].Vancouver,BC,Canada:IEEE,2007:1-6.
Wang Ling,Liu Yunhui,Wan Jianwei.Bearings-only cooperative localization algorithm of multi-robots[J].Journal of Transducer Technology,2007,20(4):794-799.
[4]Bailey T,Bryson M,Mu H,et al.Decentralised cooperative localisation for heterogeneous teams of mobile robots[A].IEEE International Conference on Robotics and Automation[C].Shanghai,China:IEEE,2011:2859-2865.
[5]Martinelli A,Pont F,Siegwart R.Multi-robot localization using relative observations[A].IEEE International Conference on Robotics and Automation[C].Barcelona,Spain:IEEE,2005:2797-2802.
[6]Fox D,Burgard W,Kruppa H,et al.Collaborative multi-robot localization[J].Autonomous Robots on Heterogeneous Multirobot Systems,2000,8(3):325-344.
[7]Howard A,Mataric M J,Sukhatme G S.Cooperative relative localization for mobile robot teams:an ego-centric approach[A].Proceedings of Naval Research Laboratory Workshop on Multi-Robot Systems[C].Washington,D C,USA:Springer,2003:65-76.
[8]Shi Xingxi,Wang Tiesheng,Huang Bo,et,al.Cooperative multi-robot localization based on distributed UKF[A].IEEE International Conference on Computer Science and Information Technology[C].Chendu,China:IEEE,2010:590-593.
Lu Jian,Xu Deming,Zhang Lichuan,et al.Cooperative localization utilizing Sigma-point Kalman filters for UUVs[J].Computer Engineering and Applications,2011,47(33):1-6.
Shi Xingxi,Zhao Chunxia,Guo Jianhui.Algorthim of CUKF and its application to mobile robot integrated navigation[J].Journal of Nanjing University of Science and Technology,2009:33(1):37-41.
Li Maohai,Hong Bingrong.Novel method of mobile robot simultaneous localization and mapping[J].Journal of Nanjing University of Science and Technology,2006:30(3):302-306.
[12]Rekleitis I M,Dudek G,Milios E E.Multi-robot cooperative localization:a study of trade-offs between efficiency and accuracy[A].IEEE/RSJ International Conference on Intelligent Robots and Systems[C].Lausanne,Switzerland:IEEE,2002:2690-2695.
Wu Panlong,Kong Jianshou.Underwater bearing-only target tracking based on square-root UKF[J].Journal of Nanjing University of Science and Technology,2009,33(6):751-755.
[14]Gustavson F G,Wasniewski J,Dongarra J J,et al.Level-3 Cholesky factorization routines improve performance of many Cholesky algorithm[J].ACM Transactions on Mathematical Software,2013,39(2):9:1-9:10.
Zhang Zhaoyou,Hao Yanling,Wu Xu.Complexity analysis for three kinds of deterministic sampling nonlinear filtering algorithm[J].Journal of Harbin Institute of Technology,2013,45(12):112-115.


Last Update: 2015-08-31