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

fYear

2004

fDate

14-17 June 2004

Firstpage

631

Lastpage

635

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Vehicles Symposium, 2004 IEEE

Print_ISBN

0-7803-8310-9

Type

conf

DOI

10.1109/IVS.2004.1336457

Filename

1336457