Study on multi-sensor data fusion for the wheeled mobile robot

Author

Li, Yan ; Feng Gao ; Lin, Tingqi ; Zheng, Jianming

Author_Institution

Sch. of Mech. Eng., Xi´´an Jiaotong Univ., China

Volume

5

fYear

2004

Firstpage

4623

Abstract

The usual method for estimating the posture of a wheeled mobile robot is dead-reckoning algorithm. However, it has the problem of gradual error accumulation due to slippage of wheels and measurement noise. To enhance the positioning precision for mobile robots, the information fusion method using Extended Kalman Filter algorithm is investigated in which multi-sensor data are provided by internal sensors such as odometers and external sensor such as laser scanner. Practical path-tracking experiment shows that the estimated posture by this system is precise to be useful.

Keywords

Kalman filters; mobile robots; optical scanners; position control; sensor fusion; dead reckoning algorithm; extended Kalman filter algorithm; external sensor; information fusion method; internal sensor; laser scanner; measurement noise; mobile robots; multi sensor data fusion; odometers; path tracking; positioning precision; posture estimation; wheel slippage; wheeled mobile robot; Computer errors; Instruments; Laser fusion; Laser noise; Mechanical engineering; Mobile robots; Noise measurement; Sensor fusion; Wheels;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on

Print_ISBN

0-7803-8273-0

Type

conf

DOI

10.1109/WCICA.2004.1342395

Filename

1342395