References
- O. Gumus, M. Topaloglu, and D. Ozcelik, “The Use of Computer Controlled Line Follower Robots in Public Transport,” Procedia Comput. Sci., vol. 102, no. August, 2016, pp. 202–208, doi: 10.1016/j.procs.2016.09.390.
- A. Latif, H. A. Widodo, R. Rahim, and K. Kunal, “Implementation of Line Follower Robot Based Microcontroller atmega32a,” J. robot. Control, vol. 1, no. 3, 2020, pp. 70–74, doi: 10.18196/jrc.1316.
- M. Antony, M. Parameswaran, N. Mathew, V.S. Sajithkumar, J. Joseph, and C.M. Jacob, “Design And Implementation Of Automatic Guided Vehicle For Hospital Application,” Proc. 5th Int. Conf. Commun. Electron. Syst. ICCES 2020, no. Icces, 2020, pp. 1031–1036, doi: 10.1109/ICCES48766.2020.09137867.
- O.F. Gómez and U. E. Gómez, “Kinematic Simulation Of A Line Follower Robot For The Creation Of The Programming Videogame Rusty Roads In The Unity Framework,” Inf. Tecnol., vol. 28, no. 5, 2017, pp. 55–64, doi: 10.4067/s0718-07642017000500008.
- A. Aharari and Y. Ueda, “Low Pass Filter Applied to Color Sensor of Line Follower Robot,” Procedia Computer Science, vol. 154, 2018, pp. 693–698, doi: 10.1016/j.procs.2019.06.108.
- V.G.R. Caitite, D.M.G. Dos Santos, I.C. Gregorio, W.B. Da Silva, and V.F. Mendes, “Diffusion Of Robotics Through Line Follower Robots,” Proc. – 15th Lat. Am. robot. Symp. 6th Brazilian robot. Symp. 9th Work. robot. Educ. LARS/SBR/WRE 2018, 2018, pp. 604–609, doi: 10.1109/LARS/S BR/WRE.2018.00109.
- H. A. Calderón, C. Mejía, and L. Cobo, “Implementación De Un Robot Móvil Seguidor De Línea Y Detector De Obstáculos Con Comunicación Bluetooth,” Review Ontare, vol. 4, no. 2, 2017, pp. 99–118, doi: 10.21158/23823399.v4.n2.20 16.1639.
- S. Kokare, “Using ZigBee,” 2018 Fourth Int. Conf. Comput. Commun. Control Autom., 2018, pp. 1–5.
- J. Chaudhari, A. Desai, and S. Gavarskar, “Line following Robot Using Arduino For Hospitals,” 2019 2nd Int. Conf. Intell. Commun. Comput. Tech. ICCT 2019, 2019, pp. 330–332, doi: 10.1109/IC CT46177.2019.8969022.
- W.K. Born and C.J. Lowrance, “Application of Convolutional Neural Network Image Classification for a Path-Following Robot,” 2018 IEEE MIT Undergrad. Res. Technol. Conf. URTC 2018, 2018, pp. 11–14, doi: 10.1109/URTC45901.2018.9244781.
- C.F. Hsu, C.T. Su, W.F. Kao, and B.K. Lee, “Vision- Based Line-Following Control of a Two-Wheel Self-Balancing Robot,” Proc. - Int. Conf. Mach. Learn. Cybern., vol. 1, 2018, pp. 319–324, doi: 10.1109/ICMLC.2018.8526952.
- J. Sarwade, S. Shetty, A. Bhavsar, M. Mergu, and A. Talekar, “Line Following Robot Using Image Processing,” Proc. 3rd Int. Conf. Comput. Methodol. Commun. ICCMC 2019, no. Iccmc, 2019, pp. 1174–1179, doi: 10.1109/ICCMC.2019.8819826.
- R. Javanmard, A.H. Zabbah, M. Karimi, and K. Jeddisaravi, “Line Following Autonomous Driving Robot Using Deep Learning,” 6th Iran. Conf. Signal Process. Intell. Syst. ICSPIS 2020, 2020, doi: 10.1109/ICSPIS51611.2020.9349547.
- A. Moulay, F. Laoufi, T. Benslimane, and O. Abdelkhalek, “FPGA-Based Car-Like Robot Path Follower with Obstacle Avoidance,” Proc. 2020 Int. Conf. Math. Inf. Technol. ICMIT 2020, 2020, pp. 125–131, doi: 10.1109/ICMIT47780.2020. 9047008.
- A. Ghorbel, N. Ben Amor, and M. Jallouli, “Design Of A Flexible Reconfigurable Mobile Robot Localization System Using FPGA Technology,” SN Applied Science, vol. 2, no. 7, 2020, doi: 10.1007/s42452-020-2960-4.
- M.A. Kader, M.Z. Islam, J. Al Rafi, M.R. Islam, and F.S. Hossain, “Line Following Autonomous Office Assistant Robot with PID Algorithm,” 2018 Int. Conf. Innov. Sci. Eng. Technol. ICISET 2018, no. October, 2018, pp. 109–114, doi: 10.1109/ICISET.2018.8745606.
- D. Nikolov, G. Zafirov, I. Stefanov, K. Nikov, and S. Stefanova, “Autonomous Navigation And Speed Control For Line Following Robot,” 2018 IEEE 27th Int. Sci. Conf. Electron. 2018 - Proc., 2018, pp. 1–4, doi: 10.1109/ET.2018.8549580.
- X. Wu, P. Jin, T. Zou, Z. Qi, H. Xiao, and P. Lou, “Backstepping Trajectory Tracking Based on Fuzzy Sliding Mode Control for Differential Mobile Robots,” Journal of Intelligent Robotics, vol. 96, no. 1, 2019, pp. 109–121, doi: 10.1007/s10846-019-00980-9.
- M. S. Gharajeh and H. B. Jond, “Speed Control For Leader-Follower Robot Formation Using Fuzzy System And Supervised Machine Learning,” Sensors, vol. 21, no. 10, 2021, pp. 1–14, doi: 10.3390/s21103433.
- S. Tayal, H.P.G. Rao, S. Bhardwaj, and H. Aggarwal, “Line Follower Robot: Design and Hardware Application,” ICRITO 2020 - IEEE 8th Int. Conf. Reliab. Infocom Technol. Optim. (Trends Futur. Dir.), 2020, pp. 10–13, doi: 10.1109/ICRITO48 877.2020.9197968.
- I.P. Latini, W.E. Barioni, M. Teixeira, F. Neves-Jr., and L.V.R. de Arruda, “Comparison between Line-Followers and Free Movement Robots in Tasks Execution in a Simulated Environment,” in 2022 Latin American Robotics Symposium (LARS), 2022 Brazilian Symposium on Robotics (SBR), and 2022 Workshop on Robotics in Education (WRE), 2022, pp. 145–150. doi: 10.1109/LARS/SBR/WRE56824.2022.9995776.
- R. Farkh, K. Al Jaloud, S. Alhuwaimel, M. T. Quasim, and M. Ksouri, “A Deep Learning Approach For The Mobile-Robot Motion Control System,” Intelligent Automation & Soft Computing, vol. 29, no. 2, 2021, pp. 423–435, doi: 10.32604/iasc.2021.016219.
- A. Roy and M.M. Noel, “Design Of A High- Speed Line Following Robot That Smoothly Follows Tight Curves,” Computer and Electrical Engineering, vol. 56, 2016, pp. 732–747, doi: 0.1016/j.compeleceng.2015.06.014.
- B. G. Fernández et al., “Robotics vs. Game- Console-Based Platforms to Learn Computer Architecture,” IEEE Access, vol. 8, 2020, pp. 95153–95169, doi: 10.1109/ACCESS.2020. 2994196.
- M.H. Nushra, Q.A. Rahman, S.M.F. Mursalin, N.B. Asad, M.M. Asif Syeed, and M.M. Islam, “Smart Car Parking With The Assistance Of Line Following Robot,” 2019 Int. Conf. Sustain. Technol. Ind. 4.0, STI 2019, vol. 0, 2019, pp. 24–25, doi: 10.1109/STI47673.2019.9068046.
- J.W. Lok, W.M.W. Muda, and A.N. Woro, “Development Of Warehouse Robot With Advanced Line Following And Background Color Sensors,” Journal of Advanced Manufacturing Technology, vol. 15, no. 2, 2021, pp. 23–34.
- H. Murcia, J.D. Valenciano, and Y. Tapiero, “Development of a Line-Follower Robot for Robotic Competition Purposes,” Applied Computer Sciences in Engineering, 2018, pp. 464–474.
- L. Screw and D. Loads, “Motor Torque Calculation,” Wire, no. 86, pp. 1–5.
- B. Zeng, J. Zhang, L. Chen, and Y. Wang, “Selfbalancing car based on ARDUINO UNO R3,” 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2018, pp. 1939–1943. doi: 10.1109/IAEAC.2018.8577775.
- R. Chai, H. Niu, J. Carrasco, F. Arvin, H. Yin, and B. Lennox, “Design and Experimental Validation of Deep Reinforcement Learning- Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment,” IEEE Trans. Neural Networks Learn. Syst., 2022, doi: 10.1109/TNNLS.2022.3209154.
- T. Guillod, P. Papamanolis, and J.W. Kolar, “Artificial Neural Network (ANN) Based Fast and Accurate Inductor Modeling and Design,” IEEE Open J. Power Electron., vol. 1, 2020, pp. 284–299, doi: 0.1109/OJPEL.2020.3012777.
