Title :
H//sub/spl infin// filter in autonomous robot navigation
Author :
Wu Wei ; Xu Xinhe ; Wang Zhongshi ; Liu Chunfang ; Ren Jiwu
Author_Institution :
Inst. of AI & Robotics, Northeastern Univ., Shenyang
Abstract :
A robust Hinfin filtering is applied to an autonomous robot navigation system for eliminating the uncertainty noise of sensors. When all the noise statistical characteristic and system model are available, Kalman filtering is an efficient algorithm. Actually, there exist many uncertain factors in real operation process of a robot. The worst is that the filter is not convergence. Simulation results proved Hinfin filtering can lower divergence, and then reduce loss of the robot as well as improve on-the-job dependability. Simulation results are given in the paper. A robot equipped with ultrasonic and laser ranger, Web-camera was used for visual tracing. Encoder is used for the dead-reckoning and correction
Keywords :
Hinfin control; Kalman filters; filtering theory; mobile robots; path planning; robot vision; statistical analysis; Hinfin filter; Kalman filtering; Web-camera; autonomous robot navigation systems; dead-reckoning; laser ranger; on-the-job dependability; sensor uncertainty noise; statistical characteristic; visual tracing; Equations; Filtering; Filters; Linear matrix inequalities; Lyapunov method; Navigation; Robots; State estimation; Uncertain systems; Uncertainty;
Conference_Titel :
Electrical and Computer Engineering, 2005. Canadian Conference on
Conference_Location :
Saskatoon, Sask.
Print_ISBN :
0-7803-8885-2
DOI :
10.1109/CCECE.2005.1557116