基于磁信标的水下SLAM方法
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摘要
水下同步定位与构图(SLAM)由于可在未知环境下实现长时间高精度导航估计,已成为近年来UUV自主导航的重要发展趋势之一。无人水下航行器(UUV)在运动过程中,以航行区域的背景地磁图为辅助提取磁信标磁场矢量和梯度特征。为增强SLAM技术在自然特征欠缺环境中的有效性,同时避免水下磁信标磁矩未知性对反演的影响,文中采用人工磁信标作为路标,为SLAM导航系统的状态更新提供观测信息。并采用张量欧拉反褶积(TED)和磁场梯度张量特征分析(EGT)相联合的反演方法对磁信标进行单点反演定位,在此基础上提出连续反演结果收敛性判定准则,准确提取磁信标与UUV之间的相对位置信息,进而构建SLAM系统的线性观测量。最后通过设计的3种磁信标分布场景对基于磁信标反演定位的SLAM系统性能开展了试验验证,基于试验结果分析了磁信标分布状态对系统性能的影响,表明了磁信标辅助方式在水下SLAM研究中的有效性。文中的研究可为UUV长航时水下安全隐蔽作业提供参考。
To improve the effectiveness of simultaneous localization and mapping(SLAM) in the areas with poor nat ural features and avoid the difficulty introduced by the unknown magnetic moments of beacons in inversion, the artificial magnetic beacons are treated as landmarks to provide observation information for state update in SLAM. The tensor Euler deconvolution and eigenanalysis of the magnetic gradient tensor(TED+EGT) approach is taken to make single-point relative position inversion during navigation. Then, a convergence judgment criteria of the continuous inversion is proposed to extract the relative positions between beacons and UUV for establishing the linear measurements in SLAM model. At last, three scenes of magnetic beacon distribution are designed to verify the effectiveness of the proposed approach. The influence of magnetic beacons' distribution on the system performance is analyzed, and the effectiveness of the approach is verified. This research may help improve UUV's ability in long-time underwater covert operations.
To improve the effectiveness of simultaneous localization and mapping(SLAM) in the areas with poor nat ural features and avoid the difficulty introduced by the unknown magnetic moments of beacons in inversion, the artificial magnetic beacons are treated as landmarks to provide observation information for state update in SLAM. The tensor Euler deconvolution and eigenanalysis of the magnetic gradient tensor(TED+EGT) approach is taken to make single-point relative position inversion during navigation. Then, a convergence judgment criteria of the continuous inversion is proposed to extract the relative positions between beacons and UUV for establishing the linear measurements in SLAM model. At last, three scenes of magnetic beacon distribution are designed to verify the effectiveness of the proposed approach. The influence of magnetic beacons' distribution on the system performance is analyzed, and the effectiveness of the approach is verified. This research may help improve UUV's ability in long-time underwater covert operations.
引文
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[2]Aulinas J,Llado X,Salvi J,et al.Selective Submap Joining for Underwater Large Scale 6-DOF SLAM[C]//The 2010IEEE/RSJ International Conference on Intelligent Robots and Systems.Taipei,Taiwan:IEEE,2010:2552-2557.
[3]He B,Liang Y,Feng X,et al.AUV SLAM and Experiments Using a Mechanical Scanning Forward-Looking Sonar[J].Sensors,2012,12(7):9386-9410.
[4]He B,Lv C,Yang L,et al.Exploration with Loop-closing in Depth-fixed Navigation for Autonomous Underwater Vehicle[C]//Intelligent Vehicles Symposium.Xi’an,China:IEEE,2009:459-463.
[5]Paull L,Huang G,Seto M,et al.Communication-constrained Multi-AUV Cooperative SLAM[C]//IEEE International Conference on Robotics and Automation.Seattle,WA,USA:IEEE,2015:509-516.
[6]Liam P,Mae S,John L.Decentralized Cooperative Trajectory Estimation for Autonomous Underwater Vehicles[C]//The 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Chicago,IL,USA:IEEE,2014.
[7]Wynn W M,Frahm C P,Clark R H.Advanced Superconducting Gradiometer Magnetometer Arrays and a Novel Signal Processing Technique[J].IEEE Transaction on Magnetics,1975,11(2):701-707.
[8]Birsan M.Recursive Bayesian Method for Magnetic Dipole Tracking With a Tensor Gradiometer[J].IEEE Transactions on Magnetics,2011,47(2):409-415.
[9]Beiki M,Pedersen L B,Nazi H.Interpretation of Aeromagnetic Data Using Eigenvector Analysis of Pseudo Gravity Gradient Tensor[J].Geophysics,2011,76(76):1-10.
[10]Clark D A.New Methods for Interpretation of Magnetic Vector and Gradient Tensor Data I:Eigenvector Analysis and the Normalised Source Strength[J].Exploration Geophysics,2012,43(4):267-282.
[11]迟铖,仸建存,吕俊伟,等.基于磁梯度张量的目标多测量点线性定位斱法[J].探测与控制学报,2017,39(5):62-67.Chi Cheng,Ren Jian-cun,LüJun-wei,et al.Linear Localization Method Based on Magnetic Gradient Tensor of Multi-points[J].Journal of Detection&Control,2017,39(5):62-67.
[12]万成彪,潘孟春,张琦,等.基于张量特征值和特征向量的磁性目标定位[J].吉林大学学报(工学版),2017,47(2):655-660.Wan Cheng-biao,Pan Meng-chun,Zhang Qi,et al.Magnetic Object Localization with Eigenvalue and Eigenvector of Tensor[J].Journal of Jilin University(Engineering and Technology Edition),2017,47(2):655-660.
[13]Zhang C,Mushayandebvu M F,Reid A B,et al.Euler Deconvolution of Gravity Tensor Gradient Data[J].Geophysics,2000,65(2):512-520.
[14]张朝阳,肖昌汉,阎辉.磁性目标的单点磁梯度张量定位斱法[J].探测与控制学报,2009,31(4):44-48.Zhang Zhao-yang,Xiao Chang-han,Yan Hui.Localization of a Magnetic Object Based on Magnetic Gradient Tensor at a Single Point[J].Journal of Detection&Control,2009,31(4):44-48.
[15]Teixeira F C,Pascoal A M.Magnetic Navigation and Tracking of Underwater Vehicles[J].IFAC Proceedings Volumes,2013,46(33):239-244.
[16]Pei Y H,Yeo H G.Magnetic Gradiometer Inversion for Underwater Magnetic Object Parameters[C]//Oceans.Singapore:IEEE,2007:1-6.
[17]Pei Y H,Yeo H G,Kang X Y,et al.Magnetic Gradiometer on an AUV for Buried Object Detection[C]//Oceans.Seattle,WA,USA:IEEE,2010:1-8.
[18]Vallivaara I,Haverinen J,Kemppainen A,et al.Magnetic Field-based SLAM Method for Solving the Localization Problem in Mobile Robot Floor-cleaning Task[C]//International Conference on Advanced Robotics.Xplore:IEEE,2011.
[19]Gao C,Harle R.MSGD:Scalable Back-end for Indoor Magnetic Field-based GraphSLAM[C]//IEEE International Conference on Robotics&Automation.Singapore,Singapore:IEEE,2017.
[20]Kok M,Solin A.Scalable Magnetic Field SLAM in 3DUsing Gaussian Process Maps[C]//2018 21st International Conference on Information Fusion,Cambridge,UK:IEEE,2018:1353-1360.
[21]Yoshii T.Method for Detecting a Magnetic Source by Measuring the Magnetic Field Thereabout.US:US4309659[P],1982.
[22]Wu M,Yao J.Adaptive UKF-SLAM Based on Magnetic Gradient Inversion Method for Underwater Navigation[C]//International Conference on Unmanned Aircraft Systems.Denver,CO,USA:IEEE,2015.