Abstract
A design of composite navigation control system based on RFID and vision is proposed for problems, such as low positioning, poor stability, high cost, of the present AGV navigation ways. AGV recognizes the station with RFID firstly, then AGV builds an image recognition system with visual technology to achieve the accurate positioning. In this way, AGV can accomplish complex navigation tasks more accurately and efficiently. Low recognition precision of guides and noise interference can be solved with software by using gray image segmentation, image edge extraction, image denoising and linear fitting. The positioning accuracy of AGV is raised to 5 mm, meanwhile the angle precision is raised to 0.1° in application. The system not only satisfies the continuous positioning in large space, but also meets the requirement of high precision positioning, and realizes industrial automation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wu, Q.: Present situation and developing trend of AGV key technology. Manufact. Autom. 35(5), 106–107 (2013)
Wu, W.: Application status and development trend of AGV autonomous guided robot. Robot Tech. Appl. 25(3), 16–17 (2012)
Hu, C.H.: Investigation of idle vehicle prepositioning strategies in an automated guided vehicle system, Ph.D. Dissertation: Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA (1995)
Agullo, J., Cardona, S., Vivancos, J.: Dynamics of vehicles with directionally sliding wheels. Mech. Mach. Theor. 24(1), 53–60 (2014)
Su, Y.: The omnidirectional mobile AGV research. Manufact. Autom. 36(8), 10–11 (2014)
Xu, W., Cai, R.: AGV assembly robot based on IPC control system design. Appl. Electron. Tech. 39(7), 131–134 (2013)
Xu, H., Zhao, Y.: Study on center line extraction for AGV’s GuidRibbon under complex conditions. Comput. Measur. Control 39(7), 131–134 (2013)
Meng, W., Liu, Z.: Research on visual guided AGV path tracking control. Control Eng. 21(3), 321–325 (2014)
Liu, G., Guo, W.: Application of improved arithmetic median filtering denoising. Comput. Eng. Appl. 46(10), 187–189 (2010)
Bonin-Font, F., Ortiz, A., Oliver, G.: Visual navigation for mobile robot: a survey. J. Intell. Rob. Syst. 53(3), 263–296 (2008)
Yun, L., Xun, D.: Image segmentation based on gray equalization and improved genetic algorithm. Comput. Eng. Appl. 47(16), 194–197 (2011)
Bhanu, B., Lee, S., Ming, J.: Adaptive image segmentation using a genetic algorithm. IEEE Trans. Syst. Man Cybenetics 25(12), 1543–1546 (1995)
Ruan, Q., Ruan, Y.: Digital Image Processing, 2nd edn. Beijing Electronic Industry Publishing House, Beijing (2003)
Lee, J.W., Kim, J.H., Lee, Y.J., Lee, K.S.: A Study on recognition of road lane and movement of vehicles for port AGV vision system. In: Proceedings of the 40th SICE Annual Conference International Session Papers, SICE 2001 (2001)
Zhang, H.: Digital Image Processing Pattern Recognition Technology and Engineering Practice. People’s Posts and Telecommunications Publishing House, Beijing (2003)
Cai, J.: Development and research of automatic vision guided vehicle. Postdoctoral research report, Zhejiang University (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, J., Wang, Y., Sheng, J., Zhang, Y., Qi, J., Yu, L. (2020). Design of AGV Positioning Navigation Control System Based on Vision and RFID. In: Kim, J., Geem, Z., Jung, D., Yoo, D., Yadav, A. (eds) Advances in Harmony Search, Soft Computing and Applications. ICHSA 2019. Advances in Intelligent Systems and Computing, vol 1063. Springer, Cham. https://doi.org/10.1007/978-3-030-31967-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-31967-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31966-3
Online ISBN: 978-3-030-31967-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)