International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Vision Sensor-Based Driving Algorithm for Indoor Automatic Guided Vehicles

  • Quan, Nguyen Van (School of Electrical Electronic and Control Engineering, Kongju National University) ;
  • Eum, Hyuk-Min (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Lee, Jeisung (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Hyun, Chang-Ho (School of Electrical Electronic and Control Engineering, Kongju National University)
  • Received : 2013.05.14
  • Accepted : 2013.06.23
  • Published : 2013.06.25
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Abstract

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

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