A Dual-Core Real-Time Embedded System for Vision-Based Automated Guided Vehicle

As a cell of Flexible Manufacturing System (FMS), Automated Guided Vehicle (AGV) is widely used in factory. In this paper, we presented a novel technology used for vision-guided AGV. An embedded dual-core processor system with Real-Time Operating System (RTOS) DSP/BIOS is designed for system manager and image processor. We adopt DSP TMS320DM642 as image processor and ARM LPC2210 as controller. The embedded RTOS DSP/BIOS is transplanted on DSP to construct a software development platform for tasks management, which enhance reliability and real-time response of system. Two CCD cameras are fixed on vehicle to capture the scene of lane. One, on the front of vehicle, is used for prediction, the other, at the center of vehicle, is used for accurate positioning. Radio Frequency Identification (RFID) reader is loaded on vehicle to collect the information stored in RFID tag which placed by the side of lane. The experimental results demonstrate the advantages of real-time and robust.

[1]  Fei-Yue Wang,et al.  An Embedded System for Vision-based Driving Environment Perception , 2006, 2006 2nd IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications.

[2]  Chang-Hoon Lee,et al.  A study for AGV steering control and identification using vision system , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[3]  Jeng-Yih Chiou.  Robot Control System Based on Distributed Embedded Systems , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[4]  Francesco Zanichelli,et al.  Vision-based line tracking and navigation in structured environments , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[5]  Emil M. Petriu,et al.  Automated guided vehicle position recovery , 1990 .

[6]  Xavier Armangué,et al.  A comparative review of camera calibrating methods with accuracy evaluation , 2002, Pattern Recognit..

[7]  Subhash Challa,et al.  Recent Developments in Vision Based Target Tracking for Autonomous Vehicles Navigation , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[8]  B. Michaelis,et al.  Real-time vehicle and lane detection with embedded hardware , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[9]  Jun Yu,et al.  An Intelligent Real-Time Monocular Vision-Based AGV System for Accurate Lane Detecting , 2008, 2008 ISECS International Colloquium on Computing, Communication, Control, and Management.

[10]  In-So Kweon,et al.  Color landmark based self-localization for indoor mobile robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[11]  Jianwei Zhang,et al.  Towards intelligent autonomous vision systems - smart image processing for robotic applications - , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).