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.
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;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Weihai
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.305802