Title :
Position estimation for a mobile robot using vision and odometry
Author :
Chenavier, Frédéric ; Crowley, James L.
Author_Institution :
LETI-DSYS, CEA-CENG, Grenoble, France
Abstract :
The authors describe a method for locating a mobile robot moving in a known environment. This technique combines position estimation from odometry with observations of the environment from a mobile camera. Fixed objects in the world provide landmarks which are listed in a database. The system calculates the angle to each landmark and then orients the camera. An extended Kalman filter is used to correct the error between the observed and estimated angle to each landmark. Results from experiments in a real environment are presented
Keywords :
Kalman filters; computer vision; distance measurement; mobile robots; navigation; position control; extended Kalman filter; landmarks; localisation; mobile robot; navigation; odometry; position estimation; robot vision; Cameras; Data mining; Error correction; Image processing; Kalman filters; Mathematical analysis; Mobile robots; Navigation; Robot vision systems; Vehicles;
Conference_Titel :
Robotics and Automation, 1992. Proceedings., 1992 IEEE International Conference on
Conference_Location :
Nice
Print_ISBN :
0-8186-2720-4
DOI :
10.1109/ROBOT.1992.220052