An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism

Sy-Hung Bach, Soo-Yeong Yi

Abstract


Recently, there has been increasing attention paid to AGV (Automated Guided Vehicle) in factories and warehouses to enhance the level of automation. In order to improve productivity, it is necessary to increase the efficiency of the AGV, including working speed and accuracy. This study presents a fuzzy-PID controller for improving the efficiency of a line-following AGV. A line-following AGV suffers from tracking errors, especially on curved paths, which causes a delay in the lap time. The fuzzy-PID controller in this study mimics the principle of human vehicle control as the situation-aware speed adjustment on curved paths. Consequently, it is possible to reduce the tracking error of AGV and improve its speed. Experimental results show that the Fuzzy-PID controller outperforms the PID controller in both accuracy and speed, especially the lap time of a line-following AGV is enhanced up to 28.6% with the proposed fuzzy-PID controller compared to that with the PID controller only.

Keywords


Fuzzy-PID; Kinematic model; Line-following AGV; Line detection;

Full Text:

PDF

References


A. Ma’arif, A. A. Nuryono, and Iswanto, "Vision-Based Line Following Robot in Webots," 2020 FORTEI-International Conference on Electrical Engineering (FORTEI-ICEE), 2020, pp. 24-28, doi: 10.1109/FORTEI-ICEE50915.2020.9249943.

M. A. Putra, E. Pitowarno, and A. Risnumawan, "Visual servoing line following robot: Camera-based line detecting and interpreting," 2017 Inter. Electronics Symposium on Engg. Tech. and Appli. (IES-ETA), 2017, pp. 123-128, doi: 10.1109/ELECSYM.2017.8240390.

I. U. Haque, A. A. Arabi, S. Hossain, T. Proma, N. Uzzaman, and M. A. Amin, "Vision based trajectory following robot and swarm," 2017 2nd International Conference on Control and Robotics Engineering (ICCRE), 2017, pp. 35-38, doi: 10.1109/ICCRE.2017.7935037.

M. V. Gomes, L. A. Bássora, O. Morandin, and K. C. T. Vivaldini, "PID control applied on a line-follower AGV using a RGB camera," 2016 IEEE 19th International Conf. on Intelligent Transportation Systems (ITSC), 2016, pp. 194-198, doi: 10.1109/ITSC.2016.7795553.

M. Auzan, R. M. Hujja, M. R. Fuadin, and D. Lelono "Path Tracking and Position Control of Nonholonomic Differential Drive Wheeled Mobile Robot," Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), vol. 7, no. 3, pp. 368-379, 2021, doi: 10.26555/jiteki.v7i3.21017.

Y. Wang, Z. Miao, H. Zhong, and Q. Pan, "Simultaneous Stabilization and Tracking of Nonholonomic Mobile Robots: A Lyapunov-Based Approach," in IEEE Trans. on Control Systems Technology, vol. 23, no. 4, pp. 1440-1450, July 2015, doi: 10.1109/TCST.2014.2375812.

M. Gupta, S. Kumar, L. Behera, and V. K. Subramanian, "A Novel Vision-Based Tracking Algorithm for a Human-Following Mobile Robot," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 7, pp. 1415-1427, July 2017, doi: 10.1109/TSMC.2016.2616343.

M. Boumehraz, Z. Habba, R. Hassani, "Vision based tracking and interception of moving target by mobile robot using fuzzy control," Journal of Applied Engineering Science & Technology, vol. 4, no. 2, pp. 159-165, 2018.

F. Abdessemed, K. Benmahammed, and E. Monacelli, "A fuzzy-based reactive controller for a non-holonomic mobile robot," Robotics and autonomous Systems, vol. 47, no. 1, pp. 31-46, 2004, doi: 10.1016/j.robot.2004.02.006.

R. El Harabi, S. B. Ali Naoui, and M. N. Abdelkrim, "Fuzzy control of a mobile robot with two trailers," 2012 First International Conference on Renewable Energies and Vehicular Technology, pp. 256-262, 2012, doi: 10.1109/REVET.2012.6195280.

A. Ouda and A. Mohamed, “Autonomous fuzzy heading control for a multi-wheeled combat vehicle,” International Journal of Robotics and Control Systems, vol. 1, no. 1, pp. 90–101, 2021, doi: 10.31763/ijrcs.v1i1.286.

O. Mohareri, R. Dhaouadi, and A.B. Rad, "Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks," Neurocomputing, vol. 88, pp. 54-66, 2012, doi: 10.1016/j.neu-com.2011.06.035.

P. S. Pratama, T. H. Nguyen, H. K. Kim, D. H. Kim, and S. B. Kim, "Positioning and obstacle avoidance of automatic guided vehicle in partially known environment," International Journal of Control, Automation and Systems, vol. 14, no. 6, pp. 1572-1581, 2016, doi: 10.1007/s12555-014-0553-y.

B. Soysal, "Real-time control of an automated guided vehicle using a continuous mode of sliding mode control," Turkish Journal of Electrical Engineering & Computer Sciences, vol. 22, no. 5, pp. 1298-1306, 2014.

I. Hassani, I. Ergui, and C. Rekik, “Turning Point and Free Segments Strategies for Navigation of Wheeled Mobile Robot,” International Journal of Robotics and Control Systems, vol. 2, no. 1, pp. 172-186, 2022, doi: 10.31763/ijrcs.v2i1.586.

P. Petrov and F. Nashashibi, "Modeling and Nonlinear Adaptive Control for Autonomous Vehicle Overtaking," in IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 4, pp. 1643-1656, Aug. 2014, doi: 10.1109/TITS.2014.2303995.

K. Fan, Q. Yang, P. Li, and W. Yan, "On the design of AGV obstacle avoidance system based on fuzzy-PID dual-mode controller," 2012 IEEE Conference on Control, Systems & Industrial Informatics, 2012, pp. 54-58, doi: 10.1109/CCSII.2012.6470473.

F. Gul, S. S. N Alhady, and W. Rahiman, "A review of controller approach for autonomous guided vehicle system," Indonesian Journal of Electrical Engineering and Computer Science, vol. 20, no. 1, pp. 552-562, 2020.

A. P. Vancea and I. Orha, "A survey in the design and control of automated guided vehicle systems," Carpathian Journal of Electronic and Computer Engineering, vol. 12, no. 2, pp. 41-49, 2019.

G. Eleftheriou, L. Doitsidis, Z. Zinonos, and S. A. Chatzichristofis, "A Fuzzy Rule-Based Control System for Fast Line-Following Robots," 2020 16th Inter. Conf. on Distributed Com. in Sensor Sys. (DCOSS), 2020, pp. 388-395, doi: 10.1109/DCOSS49796.2020.00068.

Silvirianti, A. S. R Krisna, A. Rusdinar, S. Yuwono, and R. Nugraha, "Speed control system design using fuzzy-pid for load variation of automated guided vehicle (AGV)," 2017 2nd International Conference on Frontiers of Sensors Technologies (ICFST), 2017, pp. 426-430, doi: 10.1109/ICFST.2017.8210549.

Q. Jia, C. Chang, S. Liu, L. Zhang, and S. Zhang, "Motion Control of Omnidirectional Mobile Robot Based on Fuzzy PID," 2019 Chinese Control and Decision Conference (CCDC), 2019, pp. 5149-5154, doi: 10.1109/CCDC.2019.8833047.

M. J. Mohamed, M. Y. Abbas, "Design a fuzzy pid controller for trajectory tracking of mobile robot," Engineering and Technology Journal, vol. 36, part A, no. 1, 2018, doi: 10.30684/etj.36.1A.15.

X. Zhou, T. Chen and Y. Zhang, "Research on Intelligent AGV Control System," 2018 Chinese Automation Congress (CAC), 2018, pp. 58-61, doi: 10.1109/CAC.2018.8623384.

M. S. Masmoudi, N. Krichen, M. Masmoudi, and N. Derbel, "Fuzzy logic controllers design for omnidirectional mobile robot navigation," Applied soft computing, vol. 49, pp. 901-919, 2016, doi: 10.1016/j.asoc.2016.08.057.

A. J. Moshayedi, A. S. Roy, and L. Liao, "PID Tuning Method on AGV (automated guided vehicle) Industrial Robot," Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering, vol. 12, no. 4, pp. 53-66, 2019.

A. J. Moshayedi, J. Li and L. Liao, "Simulation study and PID Tune of Automated Guided Vehicles (AGV)," 2021 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2021, pp. 1-7, doi: 10.1109/CIVEMSA52099.2021.9493679.

N. Zijie, L. Qiang, C. Yonjie, et al., "Fuzzy control strategy for course correction of omnidirectional mobile robot," International Journal of Control, Automation and Systems, vol. 17, no. 9, pp. 2354-2364, 2019, doi: 10.1007/s12555-018-0633-5.

T. Wang and C. Chang, "Hybrid Fuzzy PID Controller Design for a Mobile Robot," 2018 IEEE Inter. Conf. on Applied Sys. Invention (ICASI), 2018, pp. 650-653, doi: 10.1109/ICASI.2018.8394340.

X. Li, C. Luo, Y. Xu, and P. Li, "A Fuzzy PID controller applied in AGV control system," 2016 International Conference on Advanced Robotics and Mechatronics (ICARM), 2016, pp. 555-560, doi: 10.1109/ICARM.2016.7606981.

D. Driankov and A. Saffiotti, Fuzzy logic techniques for autonomous vehicle navigation, Physica, 2013.

L. A Zadeh, "Fuzzy sets as a basis for a theory of possibility," Fuzzy sets and systems, vol. 1, no. 1, pp. 3-28, 1978.

A. Sanjaya, H. Mawengkang, S. Efendi, and M. Zarlis, "Stability of Line Follower Robots with Fuzzy Logic and Kalman Filter Methods," Journal of Physics: Conference Series, IOP Publishing, pp. 012-016, 2019.

Y. Kanayama, Y. Kimura, F. Miyazaki, and T. Noguchi, "A stable tracking control method for an autonomous mobile robot," Proceedings., IEEE Inter. Conf. on Robotics and Automation, 1990, pp. 384-389 vol.1, doi: 10.1109/ROBOT.1990.126006.

ntrexgo.com [Internet]. Seoul (South Korea); [cited 2013 Nov]. Available from: http://www.ntrexgo.com/wp-content/uploads/2013/1-1/Stella-B3-User-Manual-v1.00.pdf




DOI: https://doi.org/10.18196/jrc.v3i4.14787

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Sy-Hung Bach, Soo-Yeong Yi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 

Journal of Robotics and Control (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com

Kuliah Teknik Elektro Terbaik