Sensor-data-fusion for an autonomous vehicle using a Kalman-filter

Author

Kasper, Roland ; Schmidt, Stephan

Author_Institution

Otto-von-Guericke Univ. Magdeburg, Magdeburg

fYear

2008

fDate

26-27 Sept. 2008

Firstpage

1

Lastpage

5

Abstract

This paper presents a method to estimate the system-state, especially the full position, of an autonomous vehicle using sensor data fusion of redundant position signals based on an extended Kalman-filter. The position is detected with the help of magnet sensors attached at the vehicle and a global camera signal with low resolution, similar to GPS. A lane marked with permanent magnets and an infrared camera are used for this purpose. The vehiclepsilas driving dynamics are described using a nonlinear single-track model.

Keywords

Kalman filters; permanent magnets; road traffic; road vehicles; sensor fusion; vehicle dynamics; autonomous vehicle; extended Kalman filter; infrared camera; magnet sensors; nonlinear single-track model; permanent magnets; sensor-data-fusion; vehicle driving dynamics; Cameras; Global Positioning System; Magnetic sensors; Mobile robots; Permanent magnets; Remotely operated vehicles; Sensor fusion; Sensor systems; Signal resolution; Vehicle detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Informatics, 2008. SISY 2008. 6th International Symposium on

Conference_Location

Subotica

Print_ISBN

978-1-4244-2406-1

Electronic_ISBN

978-1-4244-2407-8

Type

conf

DOI

10.1109/SISY.2008.4664905

Filename

4664905