DocumentCode
3457132
Title
Research on Integrated Navigation Technology of Field Robot
Author
Zhu, Feng-chun ; Ju, Yan-bing ; Wang, Ai-hua
Author_Institution
Sch. of Inf. & Electr. Eng., Shandong Univ. of Sci. & Technol.
fYear
2006
fDate
20-23 Aug. 2006
Firstpage
59
Lastpage
64
Abstract
This paper introduced GPS/INS integrated navigation technology into field robot navigation system, and mainly discussed the data fusion algorithm based on fuzzy adaptive Kalman filter. For the reason that classical Kalman filter might lead to divergence of system state parameter estimation when it dealt with time varied statistic of measurement noise in different working conditions, then by monitoring the variation grade of the actual residual compared with filter residual, the novel algorithm could adjust recursively the measurement noise covariance of Kalman filter online to make it close to real measurement covariance gradually. As a result, the Kalman filter performs optimally and the accuracy of the navigation system is improved. The simulation result also proves that this fuzzy adaptive Kalman filter works better than the conventional filtering algorithm
Keywords
Global Positioning System; adaptive Kalman filters; inertial navigation; mobile robots; path planning; sensor fusion; GPS integrated navigation technology; Global Positioning System; INS integrated navigation technology; data fusion algorithm; field robot; fuzzy adaptive Kalman filter; inertial navigation system; measurement noise covariance; system state parameter estimation; Condition monitoring; Employee welfare; Filters; Fuzzy systems; Global Positioning System; Navigation; Noise measurement; Parameter estimation; Robots; Statistics; Kalman filter; data fusion; fuzzy adaptive filter; navigation;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2006 IEEE International Conference on
Conference_Location
Weihai
Print_ISBN
1-4244-0528-9
Electronic_ISBN
1-4244-0529-7
Type
conf
DOI
10.1109/ICIA.2006.305802
Filename
4097735
Link To Document