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http://dx.doi.org/10.5302/J.ICROS.2008.14.8.800

Localization of Outdoor Wheeled Mobile Robots using Indirect Kalman Filter Based Sensor fusion  

Kwon, Ji-Wook (아주대학교 전자공학부)
Park, Mun-Soo (아주대학교 전자공학부)
Kim, Tae-Un (아주대학교 전자공학부)
Chwa, Dong-Kyoung (아주대학교 전자공학부)
Hong, Suk-Kyo (아주대학교 전자공학부)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.14, no.8, 2008 , pp. 800-808 More about this Journal
Abstract
This paper presents a localization algorithm of the outdoor wheeled mobile robot using the sensor fusion method based on indirect Kalman filter(IKF). The wheeled mobile robot considered with in this paper is approximated to the two wheeled mobile robot. The mobile robot has the IMU and encoder sensor for inertia positioning system and GPS. Because the IMU and encoder sensor have bias errors, divergence of the estimated position from the measured data can occur when the mobile robot moves for a long time. Because of many natural and artificial conditions (i.e. atmosphere or GPS body itself), GPS has the maximum error about $10{\sim}20m$ when the mobile robot moves for a short time. Thus, the fusion algorithm of IMU, encoder sensor and GPS is needed. For the sensor fusion algorithm, we use IKF that estimates the errors of the position of the mobile robot. IKF proposed in this paper can be used other autonomous agents (i.e. UAV, UGV) because IKF in this paper use the position errors of the mobile robot. We can show the stability of the proposed sensor fusion method, using the fact that the covariance of error state of the IKF is bounded. To evaluate the performance of proposed algorithm, simulation and experimental results of IKF for the position(x-axis position, y-axis position, and yaw angle) of the outdoor wheeled mobile robot are presented.
Keywords
localization; outdoor wheeled mobile robot; indirect Kalman filter; sensor fusion;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By SCOPUS : 1
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