Positioning and Obstacle Avoidance of Automatic Guided Vehicle in Partially Known Environment

• Published in: International journal of control, automation, and systems 2016, Automation, and Systems, 14(6), , pp.1572-1581
• Main Authors: 김상봉, Pandu Sandi Pratama, Trong-Hai Nguyen, 김대환, 김학경
• Format: Article
• Language: English
• Subjects: 제어계측공학
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-015-0128-6

This paper presents positioning and obstacle avoidance of Automatic Guidance Vehicle (AGV) in partiallyknown environment. To do this task, the followings are done. Firstly, the system configuration of AGV isdescribed. Secondly, mathematical kinematic modeling of the AGV is presented to understand its characteristicsand behavior. Thirdly, the Simultaneous Localization and Mapping (SLAM) algorithm based on the laser measurementsystem and encoders is proposed. The encoders are used for detecting the motion state of the AGV. In aslippery environment and a high speed AGV condition, encoder positioning method generates big error. Therefore,Extended Kalman Filter (EKF) is used to get the best position estimation of AGV by combining the encoder positioningresult and landmark positions obtained from the laser scanner. Fourthly, to achieve the desired coordinate,D* Lite algorithm is used to generate a path from the start point to the goal point for AGV and to avoid unknownobstacles using information obtained from laser scanner. A backstepping controller based on Lyapunov stability isproposed for tracking the desired path generated by D* Lite algorithm. Finally, the effectiveness of the proposed algorithmsand controller are verified by using experiment. The experimental results show that the AGV successfullyreaches the goal point with an acceptable small error. KCI Citation Count: 13