Noise covariance identification based adaptive UKF with application to mobile robot systems

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	Noise covariance identification based adaptive UKF with application to mobile robot systems
	Song Q(宋崎); Jiang Z(姜哲); Han JD(韩建达)
	2007
会议名称	IEEE International Conference on Robotics and Automation
会议日期	April 10-14, 2007
会议地点	Rome, ITALY
页码	4164-4169
中文摘要	A novel adaptive Unscented Kalman Filter (UKF) based on dual estimation structure is proposed. The filter is composed of two parallel master-slave UIKFs, while the master one estimates the states and the slave one estimates the diagonal elements of the noise covariance matrix for the master UKF. By estimating the noise covariance online, the proposed method 1 able to compensate the errors resulting from the change of the noise statistics. Such a mechanism improves the adaptive ability of the UKF and enlarges its application scope. Simulations conducted on the dynamics of an omni-directional mobile robot indicate that the performance of the adaptive UKF is superior to the standard one in terms of fast convergence and estimation accuracy.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	IEEE
会议录	PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-10
会议录出版者	IEEE
会议录出版地	NEW YORK
语种	英语
ISSN号	1050-4729
ISBN号	978-1-4244-0601-2
WOS记录号	WOS:000250915304027
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/8806]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Song Q,Jiang Z,Han JD. Noise covariance identification based adaptive UKF with application to mobile robot systems[C]. 见:IEEE International Conference on Robotics and Automation. Rome, ITALY. April 10-14, 2007.