室内UWB/LiDAR组合定位算法
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摘要
针对室内定位中UWB受非视距影响明显以及LiDAR SLAM算法误差累积的问题,提出一种UWB/LiDAR组合定位算法,即将UWB测距信息、LiDAR SLAM的位移增量和角度观测值作为量测值,利用扩展卡尔曼滤波进行参数解算。实验结果表明:UWB/LiDAR组合定位系统能有效抑制非视距影响和SLAM算法误差累积;相对于单一传感器,UWB/LiDAR组合定位系统能稳定地提供厘米级定位精度。
Aiming at the problem that it is susceptible to non-line-of-sight for UWB and error accumulation for LiDAR SLAM algorithm in indoor positioning,the paper proposed a combined positioning algorithm of UWB/LiDAR:the ranging information of UWB,the displacement increments and angle observations of LiDAR SLAM were taken as measurement values,and the extended Kalman filter was used to calculate the parameters.Experimental result showed that the proposed method could effectively suppress the impact of non-line-of-sight and the error accumulation of SLAM algorithm;moreover,compared with the single sensor,the UWB/LiDAR combined positioning system could stably provide the positioning accuracy of centimeter-level.
Aiming at the problem that it is susceptible to non-line-of-sight for UWB and error accumulation for LiDAR SLAM algorithm in indoor positioning,the paper proposed a combined positioning algorithm of UWB/LiDAR:the ranging information of UWB,the displacement increments and angle observations of LiDAR SLAM were taken as measurement values,and the extended Kalman filter was used to calculate the parameters.Experimental result showed that the proposed method could effectively suppress the impact of non-line-of-sight and the error accumulation of SLAM algorithm;moreover,compared with the single sensor,the UWB/LiDAR combined positioning system could stably provide the positioning accuracy of centimeter-level.
引文
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[13]郭剑辉,赵春霞.一种新的粒子滤波SLAM算法[J].计算机研究与发展,2008,45(5):853-860.
[14]丁鸿蒙.基于EKF的自主式水下航行器SLAM方法研究[D].哈尔滨:哈尔滨工程大学,2014.
[15]薛永胜,王姮,张华,等.EKF-SLAM算法的改进及其在Turtlebot的实现[J].西南科技大学学报,2015,30(1):54-59.
[16]薛长虎,聂桂根,汪晶.扩展卡尔曼滤波与粒子滤波性能对比[J].测绘通报,2016(4):10-14.
[2]吴富梅.GNSS/INS组合导航误差补偿与自适应滤波理论的拓展[D].郑州:信息工程大学,2010.
[3] KRNK J,STREIT J.Summary of available indoor location techniques[J].IFAC-Papers On Line,2016,49(25):311-317.
[4] PEREZ-CRUZ F,LIN C K,HUANG H.Blade:a universal,blind learning algorithm for TOA localization in NLOS channels[C]//The Institute of Electrical and Electronic Engineers(IEEE).Proceedings of 2016IEEE Globecom Workshops(GC Wkshps).Washington:IEEE,2016:1-7.
[5] ZHANG C C,BAO X Y,WEI Q L,et al.A Kalman filter for UWB positioning in LOS/NLOS scenarios[C]//The Institute of Electrical and Electronic Engineers(IEEE).Proceedings of 2016fourth International Conference on Ubiquitous Positioning,Indoor Navigation and Location Based Services(UPINLBS).Shanghai:IEEE,2016:73-78.
[6]王晓伟.基于GPS/INS组合定位系统的滤波算法的研究与仿真[D].成都:西南交通大学,2013.
[7] NILSSON J O,DE ANGELIS A,SKOG I,et al.Signal processing issues in indoor positioning by ultra wide band radio aided inertial navigation[C]//The Institute of Electrical and Electronic Engineers(IEEE).Proceedings of 2009 17th European Signal Processing Conference.Glasgow,UK:IEEE,2009:2161-2165.
[8]李奇越,吴忠,黎洁,等.基于改进卡尔曼滤波的NLOS误差消除算法[J].电子测量与仪器学报,2015,29(10):1513-1519.
[9]刘韬,徐爱功,隋心.超宽带与惯性导航组合的室内导航定位[J].测绘科学,2016,41(12):162-166.
[10]徐爱功,刘韬,隋心,等.UWB/INS紧组合的室内定位定姿方法[J].导航定位学报,2017,6(2):14-19.
[11]KOK M,HOL J D,SCHN T B.Indoor positioning using ultra wide band and inertial measurements[J].IEEE Transactions on Vehicular Technology,2015,64(4):1293-1303.
[12]DURRANT-WHYTE H,BAILEY T.Simultaneous localization and mapping:part I[J].IEEE Robotics&Automation Magazine,2006,13(2):99-110.
[13]郭剑辉,赵春霞.一种新的粒子滤波SLAM算法[J].计算机研究与发展,2008,45(5):853-860.
[14]丁鸿蒙.基于EKF的自主式水下航行器SLAM方法研究[D].哈尔滨:哈尔滨工程大学,2014.
[15]薛永胜,王姮,张华,等.EKF-SLAM算法的改进及其在Turtlebot的实现[J].西南科技大学学报,2015,30(1):54-59.
[16]薛长虎,聂桂根,汪晶.扩展卡尔曼滤波与粒子滤波性能对比[J].测绘通报,2016(4):10-14.
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