Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

Pandu , Sandi Pratama, and Sang , Kwun Jeong, and Soon , Sil Park, and Sang , Bong Kim (2013) Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology. International Journal of Science and Engineering, 4 (1). pp. 11-15. ISSN 20865023

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Official URL: http://ejournal.undip.ac.id/index.php/ijse/article...

Abstract

This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV) system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition.

Item Type:Article
Uncontrolled Keywords:Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system
Subjects:T Technology > TP Chemical technology
Divisions:Faculty of Engineering > Department of Chemical Engineering
Faculty of Engineering > Department of Chemical Engineering

UNDIP Journal > International Journal of Science and Engineering
ID Code:37693
Deposited By:teknik kimia
Deposited On:20 Dec 2012 11:11
Last Modified:25 Dec 2012 18:16

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