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WSNs下移动机器人HuberM-CKF离散滤波定位
Alternative TitleDiscrete HuberM-CKF filter based mobile robot positioning in WSNs
邓先瑞; 聂雪媛; 刘国平
Source Publication计算机应用研究
2016
Volume33Issue:6Pages:1839-1842
ISSN1001-3695
Abstract针对传统移动机器人定位算法精度不高的问题,提出一种基于无线传感器网络HurbM-CKalman滤波(HCKF)算法的移动机器人定位算法。利用HurbM极大似然估计代价函数,求解线性化后CKF观测矩阵,从而解决CKF滤波算法在未知非高斯白噪声干扰下估计精度不高的问题。然后,在体育馆基于WSNs构建了移动机器人定位实验环境,并结合移动机器人动力学模型,对HCKF、CKF算法的定位精度进行对比。结果显示,在不含噪声干扰和含未知噪声干扰两种情况下,HCKF算法定位精度分别比CKF算法提高7%和15%。
Other AbstractAccording to problem of low accuracy in traditional mobile robot localization,this paper designed the discrete HuberM- CKalmam filter (HCKF) based mobile robot positioning algorithm. It made use of the cost function of HurbM maximum likelihood estimation to solve the linearized CKF observation matrix,which improved the estimation accuracy for CKF filter algorithm with unknown-non-Gauss white noise disturbance. Then,it constructed WSNs based experiment environment for mobile robot at gymnasium,and combined with mobile robot dynamics model,it compared the positioning accuracy for the HCKF and the CKF algorithm. The results show that,for the two cases of non interference and unknown noise interference,the proposed method respectively improves the accuracy of HCKF algorithm about 7% and 15% more than CKF algorithm.
KeywordWireless Sensor Network Hurbm Cost Function Ckf Filter Mobile Robot Localization
Indexed ByCSCD
Language中文
WOS Keywordwireless sensor network ; HurbM cost function ; CKF filter ; mobile robot ; localization
Funding Organization河北省科技计划资助项目 ; 唐山师范学院博士基金资助项目
CSCD IDCSCD:5717251
DepartmentLMFS流固耦合与数值计算(LHO)
RankingFalse
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/59816
Collection流固耦合系统力学重点实验室
Recommended Citation
GB/T 7714
邓先瑞,聂雪媛,刘国平. WSNs下移动机器人HuberM-CKF离散滤波定位[J]. 计算机应用研究,2016,33(6):1839-1842.
APA 邓先瑞,聂雪媛,&刘国平.(2016).WSNs下移动机器人HuberM-CKF离散滤波定位.计算机应用研究,33(6),1839-1842.
MLA 邓先瑞,et al."WSNs下移动机器人HuberM-CKF离散滤波定位".计算机应用研究 33.6(2016):1839-1842.
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