SIA OpenIR  > 水下机器人研究室
Alternative TitleUnderwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF)
刘开周; 程大军; 李一平; 封锡盛
Rights Holder中国科学院沈阳自动化研究所
Patent Agent沈阳科苑专利商标代理有限公司 21002
Other AbstractThe invention discloses an underwater robot state and parameter joint estimation method based on self-adaption unscented Kalman filtering (UKF). The method comprises building an expanding reference model of an underwater robot, and enabling the reference model to have a dynamical model of the underwater robot and a fault model of a thruster; adopting a main filter of the self-adaption UKF to deliver and update expanding states composed of poses and speed of the underwater robot state and faults of the thruster according to pose information detected by a position sensor, and timely estimating speed information of the underwater robot and fault message of the thruster; and simultaneously adopting an accessory filter of the self-adaption UKF to timely estimate noise information of a system according to innovation information of the main filter. The underwater robot state and parameter joint estimation method has good instantaneity, can conduct joint estimation on states and parameters of the system, and can achieve high estimation accuracy when priori information of process noise and measurement noise is unknown.


PCT Attributes
Application Date2011-07-08
Date Available2014-12-10
Application NumberCN201110190512.5
Open (Notice) NumberCN102862666B
Contribution Rank1
Document Type专利
Recommended Citation
GB/T 7714
刘开周,程大军,李一平,等. 一种基于自适应UKF的水下机器人状态和参数联合估计方法[P]. 2013-01-09.
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