An Adaptive UKF Algorithm for the State and  Parameter Estimations of a Mobile Robot

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	An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot
	SONG Qi; HAN JianDa
刊名	自动化学报
	2008
卷号	000 期号:1.0 页码:72-79
关键词	卡尔曼滤波器算法移动式遥控装置状态估计参数估计过程协方差
ISSN号	0254-4156
其他题名	An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot
英文摘要	For improving the estimation accuracy and the convergence speed of the unscented Kalman filter （UKF）, a novel adaptive filter method is proposed. The error between the covariance matrices of innovation measurements and their corresponding estimations/predictions is utilized as the cost function. On the basis of the MIT rule, an adaptive algorithm is designed to update the covariance of the process uncertainties online by minimizing the cost function. The updated covariance is fed back into the normal UKF. Such an adaptive mechanism is intended to compensate the lack of a priori knowledge of the process uncertainty distribution and to improve the performance of UKF for the active state and parameter estimations. The asymptotic properties of this adaptive UKF are discussed. Simulations are conducted using an omni-directional mobile robot, and the results are compared with those obtained by normal UKF to demonstrate its effectiveness and advantage over the previous methods.
语种	中文
CSCD记录号	CSCD:3270063
内容类型	期刊论文
源URL	[http://ir.imr.ac.cn/handle/321006/148221]
专题	金属研究所_中国科学院金属研究所
作者单位	中国科学院金属研究所
推荐引用方式 GB/T 7714	SONG Qi,HAN JianDa. An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot[J]. 自动化学报,2008,000(1.0):72-79.
APA	SONG Qi,&HAN JianDa.(2008).An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot.自动化学报,000(1.0),72-79.
MLA	SONG Qi,et al."An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot".自动化学报 000.1.0(2008):72-79.