KLI

STATE ESTIMATION FOR AUTONOMOUS GUIDED VEHICLE USING THE EXTENDED KALMAN FILTER

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Abstract
This paper presents a four-wheel drive autonomous guided vehicle (AGV) system designed to transport unmanned control transportation (UCT) standard cargo containers in seaport environments. A model vehicle is simulated and experimented in laboratory and in a prepared road at speed up to 3 m/s. The navigation system is based on the use of encoder, gyro, and transponders at known locations in the environment. A general method for the construction of a positioning system is proposed, which is based on an extended Kalman filter (EKF) and commercially available navigation sensors in an absolute coordinate of AGV. The kinematics model and observation models are adapted for EKF application. Simulation result shows good performances of the AGV state estimator.
This paper presents a four-wheel drive autonomous guided vehicle (AGV) system designed to transport unmanned control transportation (UCT) standard cargo containers in seaport environments. A model vehicle is simulated and experimented in laboratory and in a prepared road at speed up to 3 m/s. The navigation system is based on the use of encoder, gyro, and transponders at known locations in the environment. A general method for the construction of a positioning system is proposed, which is based on an extended Kalman filter (EKF) and commercially available navigation sensors in an absolute coordinate of AGV. The kinematics model and observation models are adapted for EKF application. Simulation result shows good performances of the AGV state estimator.
Author(s)
Kim, Hansil
Issued Date
2002
Type
Research Laboratory
URI
https://oak.ulsan.ac.kr/handle/2021.oak/4151
http://ulsan.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002025562
Publisher
공학연구논문집
Language
eng
Rights
울산대학교 저작물은 저작권에 의해 보호받습니다.
Citation Volume
33
Citation Number
1
Citation Start Page
129
Citation End Page
144
Appears in Collections:
Research Laboratory > Engineering Research
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