[1]王碧霞,李银伢,戚国庆,等.基于SR-UKF的纯方位多移动机器人协同定位算法[J].南京理工大学学报(自然科学版),2015,39(04):440.
 Wang Bixia,Li Yinya,Qi Guoqing,et al.Bearings-only cooperative localization algorithm of multi-mobile robots based on square-root unscented Kalman filter[J].Journal of Nanjing University of Science and Technology,2015,39(04):440.
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基于SR-UKF的纯方位多移动机器人协同定位算法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
39卷
期数:
2015年04期
页码:
440
栏目:
出版日期:
2015-08-31

文章信息/Info

Title:
Bearings-only cooperative localization algorithm of multi-mobile robots based on square-root unscented Kalman filter
作者:
王碧霞李银伢戚国庆盛安冬
南京理工大学 自动化学院,江苏 南京 210094
Author(s):
Wang BixiaLi YinyaQi GuoqingSheng Andong
School of Automation,NUST,Nanjing 210094,China
关键词:
协同定位 多机器人 纯方位 平方根无迹卡尔曼滤波 不完全量测 计算复杂度 相对方位 自定位
Keywords:
cooperative localization multi-mobile robots bearings-only square-root unscented Kalman filter incomplete measurements computation complexity relative bearings self-localization
分类号:
TP242
摘要:
为了解决现有多移动机器人定位算法难以同时兼顾定位精度和实时性的问题,该文给出了一种基于相对方位的平方根无迹卡尔曼滤波(Square-root unscented Kalman filter,SR-UKF)多移动机器人协同定位算法。该方法根据机器人运动学方程和量测方程给出多移动机器人自定位的动态模型,利用相对方位作为量测值,在滤波中直接传递协方差矩阵的平方根对系统状态整体更新,实现了多机器人系统的分布式自定位。仿真结果表明:在同等条件下,SR-UKF 算法定位精度比已有算法精度提高了近一倍,单次平均运行时间减少了三分之二。
Abstract:
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.

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备注/Memo

备注/Memo:
收稿日期:2014-12-18 修回日期:2015-01-20
基金项目:国家自然科学基金(61273076,61104186); 江苏省自然科学基金(BK2012801)
作者简介:王碧霞(1990-),女,硕士生,主要研究方向:多移动观测平台协同定位,E-mail:121676318@qq.com; 通讯作者:李银伢(1976-),男,博士,副教授,主要研究方向:非线性估计理论及其工程应用,E-mail:liyinya@njust.edu.cn。
引文格式:王碧霞,李银伢,戚国庆,等.基于SR-UKF的纯方位多移动机器人协同定位算法[J].南京理工大学学报,2015,39(4):440-446.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2015-08-31