This paper is a case study of the development of a localization and positioning subsystem of an Automated Guided Vehicle-based transportation system. The described system uses primarily RFID markers for localization. In some deployments, those markers occasionally fail, mostly due to being crushed by cargo platforms operated by a human or due to internal defects. Those failures are not common enough to warrant switching from marker-based localization to a more sophisticated technique, but they require additional effort from maintenance staff. In this case study, we present our solution to this problem – a self-tuning algorithm that is able to detect marker failures and, in most cases, keep the system operational. The paper briefly discusses business circumstances under which such a solution is reasonable and then describes in detail the entire technical process, including data acquisition, verification, algorithm development and finally, the result of deploying the system in production.


Industrial control; Unmanned vehicles; Fault tolerance; Maintenance

Bandyopadhyay S.: Intelligent Vehicles and Materials Transportation in the Manufacturing Sector: Emerging Research and Opportunities. IGI Global 2017.

Campion G., Bastin G., D’Andréa-Novel B.: Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. Proceedings IEEE International Conference on Robotics and Automation (IEEE) 1993, [].

Clausing D.: Taguchi methods to improve the development process. IEEE International Conference on Communications – Spanning the Universe 2, 1988 826–832, [].

Deming W. E.: Sample Design in Business Research. Wiley-Interscience, 1990.

Dreyfus S.: An Appraisal of Some Shortest-Path Algorithms. Operations Research 17(3), 1969, [].

Ismail A. H., Ramli H. R., Ahmad M. H., Marhaban M. H.: Vision-based system for line following mobile robot. IEEE Symposium on Industrial Electronics & Applications 2009, 642–645, [].

Lee J-W., Choi S-U., Lee C-H., Lee Y-J., Lee K-S: A study for AGV steering control and identification using vision system. IEEE International Symposium on Industrial Electronics Proceedings 3, 2001, 1575–1578 (Cat. No. 01TH8570), [].

Leitner S. H., Mahnke W.: OPC UA–service-oriented architecture for industrial applications. ABB Corporate Research Center 48, 2006, 61–66.

Li L., Schultze L.: Comparison and Evaluation of SLAM Algorithms for AGV Navigation. F.-J. Villmer, E. Padoano (Eds.): Department of Production Engineering and Management. Production Engineering and Management. Lemgo 2018.

Pang Y., De La Cruz A. L., Lodewijks G.: Bipolar magnetic positioning system for automated guided vehicles. IEEE Intelligent Vehicles Symposium 2008, 883–888, [].

Park J., Kim J. Y., Kim B., Kim S.: Global Map Generation using LiDAR and Stereo Camera for Initial Positioning of Mobile Robot. International Conference on Information and Communication Technology Robotics (ICT-ROBOT), 2018, 1–4, [].

Park J., Lee J., Park Y., Kim S. W.: AGV parking system based on tracking landmark. 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology 2009, 340–343 [].

Quan S., Chen J.: AGV Localization Based on Odometry and LiDAR. 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing 2019, 483–486, [].

Ray K. A., Gupta M., Behera L., Jamshidi M.: Sonar based Autonomous Automatic Guided Vehicle (AGV) navigation. IEEE International Conference on Systems and System Engineering 2008, 1–6,[].

Wiklund U., Andersson U., Hyyppä K.: AGV navigation by angle measurements. Automated guided vehicle systems: Proceedings of the 6th International Conference 1988, 199–212.

Wang D., Low C. B.: Modeling Skidding and Slipping in Wheeled Mobile Robots: Control Design Perspective. IEEE/RSJ International Conference on Intelligent Robots and Systems 2006, 1867–1872,[].


Published : 2020-09-30

Lewowski, T. (2020). SOLVING THE FAILING TRACK MARKER PROBLEM IN AUTOMATED GUIDED VEHICLE SYSTEMS – A CASE STUDY. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 10(3), 36-43.

Tomasz Lewowski
Wrocław University of Science and Technology, Faculty of Computer Science and Management, Department of Applied Informatics, Wrocław, Poland; Octant sp. z o.o.,  Poland