Automatic guided vehicle control by vision system

AGV's control has been developed in several types. This research aims to develop the AGV's control using image processing in order to assist AGV from losing the way when the guide line is missing. The AGV, used for experiment, has three wheels. There are one wheel at the front and another two rear wheels. The front wheel is driving and steering controlled by using DC motors on each axis. An encoder is attached on steering axis which is used to check AGV orientation angle. At two rear wheels, there are also attached encoder which is used to measuring the position of AGV for controlling distance of the AGV motion. PLC is applied for AGV's control application. Wireless color CCD camera is used to be a sensor for detection line's color that is placed on the ground which is the front side of AGV. CCD sensor is applied to navigate the detected path of traveling. Red line is constructed for AGV's path. Image processing is operated for detecting the different of guide line and background. Laplacian operator method is applied for edge detection algorithm including filter and thresholding technique. Computer program will created the virtual line by using trigonometry method and sent current position data to AGV's motion controller.

[1]  Wen-Hsiang Tsai,et al.  Viewing corridors as right parallelepipeds for vision-based vehicle localization , 1999, IEEE Trans. Ind. Electron..

[2]  E.W. Frew Comparison of lateral controllers for following linear structures using computer vision , 2006, 2006 American Control Conference.

[3]  Suthep Butdee,et al.  LEANING AND RECOGNITION ALGORITHM OF INTELLIGENT AGV SYSTEM , 2006 .

[4]  S. Butdee,et al.  LOCALIZATION BASED ON MATCHING LOCATION OF AGV , 2007 .

[5]  X. Cufi,et al.  WMR navigation using local potential field corridors and narrow local occupancy grid perception , 2008, 2008 IEEE International Conference on Automation, Quality and Testing, Robotics.

[6]  Giovanni Garibotto,et al.  Computer vision control of an intelligent forklift truck , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[7]  Matthew N. Dailey,et al.  Simultaneous Localization and Mapping with Stereo Vision , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[8]  N.G. Romero,et al.  Control of a fleet of vehicles using Computer Vision, Cellular Automaton and Genetic Trained Behaviour , 2006, 2006 IEEE International Conference on Mechatronics.

[9]  Byung-Ryong Lee,et al.  New lane detection algorithm for autonomous vehicles using computer vision , 2008, 2008 International Conference on Control, Automation and Systems.

[10]  Suthep Butdee,et al.  Estimation and control of Automatic Guided Vehicle , 2009 .

[11]  Timothy W. McLain,et al.  Performance Evaluation of Vision-Based Navigation and Landing on a Rotorcraft Unmanned Aerial Vehicle , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[12]  Jun Yu,et al.  An Embedded Vehicular Controller with ARM and DSP for a Vision-Based AGV , 2008, 2008 International Conference on Embedded Software and Systems Symposia.

[13]  Frédéric Vignat,et al.  SELF-ALIGNMENT CONTROL OF AN AUTOMATED UNGUIDED VEHICLE , 2006 .