Gmiterko Alexsander , Technical University of Košice (Letna 9, 04200 Košice, Slovak Republic)

Language: english


Urgency of the research. There is a need from industrial practice for developing of methods for linefollowing navigation of automated guided vehicle (AGV) for logistic task in factories without operators.

Target setting. Various types of navigation methods are used for vehicles.

Actual scientific researches and issues analysis. Navigation of this automated guided vehicle can be made through the color line on ground or through the inductive sensed cable located underground. Also magnetically guided method is used. Various types of optical markers can be also used. Nowadays this type of autonomous robot applications grows up, because there is a need from industry.

Uninvestigated parts of general matters defining. Next generation of automated guided vehicle is navigated via using laser scanners and they are also called LGV – Laser Guided Vehicle. This type is not covered in this paper.

The research objective. The main aim of paper is to design the sensing system for color line sensing. There are several problems in using of these types of sensors. Manufacturer notes that there is placed daylight filter, but first experiments shows sensitivity to daylight. This problem can occurs when vehicle goes to tunnel. Next problem is when vehicle moves up-hill and downhill on a bridge.

The statement of basic materials. The color of sensor can be sensed with sensor - reflection optocoupler working in infrared light range. The optocoupler includes the infrared LED transmitter and infrared phototransistor, which senses the reflected light. Optocouplers are placed on bottom side of vehicle. Navigation line is black and other ground area is white. Optocoupler located over the navigation black line has no infrared reflection.

Conclusions. The selected sensor system has been adapted for line detection application. Also ramp problems have been solved. Sensors have been successfully installed on linefollower vehicle. Results shows visible difference between the voltage levels related to black and white color line. Future plans is to add camera vision system for automatic recognition of line before vehicle and continuously path planning. Vision systems are also frequently used for obstacle detection and mapping of environment and consequently for path planning.

Key words:

sensor, mobile vehicle, line, color.


1. WEASEL® auto-guided transport system. (2018). Cited 10-8-2018. Available online:  Schaefer Systems International, Inc.

2. CONSTANTIN, O. Automated Guided Vehicle. (2018). Cited 10-8-2018. Available online:

3. Automated Guided Vehicle [AGV] 3D Model.  (2018). Cited 10-8-2018. Available online:

4. MIKOVA, L., TREBUŇA, F. (2012). The Application of Simulation Methods for Modeling Mechatronic Systems. Acta Mechanica Slovaca. 16 (2), pp. 32-37.

5. NITULESCU, M. (2018). Experiments in Mobile Robot Control. Mechatronics 2008. Paper #200. Cited 04-07-2013. Available online: mecatronics2008_200.pdf.

6. BABINEC, A., DEKAN, M., DUCHON, F., et al. (2012). Modifications of VFH navigation methods for mobile robots. Procedia Engineering. 48 (2012), pp. 10-14. DOI: 10.1016/j.proeng.2012.09.478

7. DUCHON, F., HUNADY, D., DEKAN, M. et al. (2012). Optimal navigation for mobile robot in known environment. 11th International Conference on Industrial, Service and Humanoid Robotics (ROBTEP 2012) Location: Strbske Pleso, Slovakia. pp. 33. DOI: 10.4028/ AMM.1000.33.

8. SIMONOVA, A., HARGAS, L., KONIAR, D. (2017). Uses of on-off controller for regulation of higher-order system in comparator mode. Electrical Engineering. 99 (4), pp. 1367-1375. DOI: 10.1007/s00202-017-0610-7.

9. KONIAR, D., HARGAS, L., LONCOVA, Z., et al. (2017). Visual system-based object tracking using image segmentation for biomedical applications. Electrical Engineering.  99 (4), pp. 1349-1366. DOI: 10.1007/s00202-017-0609-0.

10. GMITERKO, A., VIRGALA, I., VACKOVÁ, M. (2010). Dynamic Analysis of Two-Mass System to Imitate Rectilinear Motion of a Snake. Acta Mechanica Slovaca. 14 (2). pp. 74-81.

11. DUCHOŇ, F., DEKAN, M., JURIŠICA, L., VITKO, A. (2012). Some Applications of Laser Rangefinder in Mobile Robotics. Journal of Control Engineering and Applied Informatics. 14 (2). pp. 50-57.

12. GMITERKO, A., KELEMEN, M., KELEMENOVÁ, T., MIKOVÁ, L. (2010). Adaptable Mechatronic Locomotion System. Acta Mechanica Slovaca. 14 (2). pp. 102-108.

13. HANZEL, J., DUCHOŇ, F., RODINA, J., PÁSZTÓ, P. (2013). Global Navigation Systems for Mobile Robots. International Journal of Systems Applications, Engineering & Development, 7 (5), pp. 279-285.

14. TÖLGYESSY, M., CHOVANEC, L., PÁSZTÓ, P., HUBINSKÝ, P. (2014). A Plane Based Real-Time Algorithm for Controlling a Semi-Autonomous Robot with Hand Gestures Using the Kinect. International Journal of Imaging and Robotics. 13 (2), pp. 126-133.

15. TURYGIN, Y., & BOŽEK, P. (2013). Mechatronic systems maintenance and repair management system. Transfer of innovations, 26 (2013). 3-5.

16. SPANIKOVA, G., SPANIK, P., FRIVALDSKY, M. et al. (2017). Electric model of liver tissue for investigation of electrosurgical impacts. Electrical Engineering, 99 (4). 1185-1194.

17. KARAVAEV, Y. L., & KILIN, A. A. (2016). Nonholonomic dynamics and control of a spherical robot with an internal omniwheel platform: Theory and experiments. Proceedings of the Steklov Institute of Mathematics, 295 (1), 1 November 2016, 158-167.