Title :
A simultaneous localization and mapping algorithm based on Kalman filtering
Author :
Chou, H. ; Traonmilin, M. ; Ollivier, E. ; Parent, M.
Author_Institution :
INRIA Rocquencourt, Le Chesnay, France
Abstract :
For automatic navigation of autonomous vehicles, localization in real time is a key issue. In this article, a simultaneous localization and mapping algorithm is proposed for an autonomous vehicle. We use a laser detection and ranging sensor to detect the operating environment. An environment map is plot out using the sensor output data. Then, with an odometer, the vehicle position is located on this map. Finally, these two sensor outputs are merged using a Kalman filter to correct the map as well as the vehicle position.
Keywords :
Kalman filters; data acquisition; distance measurement; filtering theory; laser ranging; mobile robots; navigation; optical sensors; road vehicles; Kalman filtering; automatic navigation; autonomous vehicles; laser detection; mapping algorithm; odometer; operating environment; ranging sensor; sensor output data; simultaneous localization; vehicle position; Bicycles; Filtering algorithms; Global Positioning System; Kalman filters; Mathematical model; Mobile robots; Remotely operated vehicles; Simultaneous localization and mapping; Sonar navigation; Wheels;
Conference_Titel :
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN :
0-7803-8310-9
DOI :
10.1109/IVS.2004.1336457
