skip to main content

Navigasi robot bergerak berdasarkan landmark garis menggunakan kontroler Braitenberg dan pengolahan citra

Mobile robot navigation based on line landmarks using the Braitenberg controller and image processing

Department of Electrical Engineering, Universitas Jember, Indonesia

Received: 20 Jan 2020; Revised: 22 Apr 2020; Accepted: 23 Apr 2020; Available online: 5 May 2020; Published: 31 Jul 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer under

Citation Format:
Line following and lane tracking are robotic navigation techniques that use lines as a guide. The techniques can be applied to mobile robots in the industry. This research applied the Braitenberg controller and image processing to control and obtain line information around the mobile robot. The robot was implemented using Arduino Uno as a controller. A webcam was connected to a computer that performs image processing using canny edge detection and sends the data to the robot controller via serial communication. The robot can navigate on the side of the line, and the success rate of the system is 100 % at a turn of 135 ° and 80 % at a turn of 90 °.
Keywords: mobile robot navigation; image processing; Braitenberg controller
Funding: Universitas Jember

Article Metrics:

  1. B. Siciliano, L. Sciavicco, G. Oriolo, and L. Villani, Robotics: modelling planning and control. Springer, 2009. doi: 10.1007/978-1-84628-642-1
  2. O. Khatib, Springer handbook of robotics. Springer, 2008
  3. M. U. Hassan, M. Ullah, and J. Iqbal, “Towards autonomy in agriculture: design and prototyping of a robotic vehicle with seed selector,” in 2nd International Conference on Robotics and Artificial Intelligence, Rawalpindi, Pakistan, Nov. 2016, pp. 37-44. doi: 10.1109/ICRAI.2016.7791225
  4. S. K. Das and M. K. Pasan, “Design and methodology of automated guided vehicle - a review,” IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), Special Issue, pp. 29-33, 2016. doi: 10.9790/1684-15010030329-35
  5. W. Tushar and S. Pranav, “Design of lane detecting and following autonomous robot,” IOSR Journal of Computer Engineering (IOSRJCE), vol. 2, no. 2, pp. 45-48, 2012. doi: 10.9790/0661-0224548
  6. A. R. Chaidir, A. B. Satriya, and G. D. Kalandro, “Design of a gripping imitator robotic arm for taking an object,” dalam 4th International Conference on Information and Communication Technology (ICoICT), Bandung, Indonesia, May 2016, pp. 1-5. doi: 10.1109/ICoICT.2016.7571940
  7. T. Ferreira and I. Gorlach, “Development of an automated guided vehicle controller using a model-based systems engineering approach,” South African Journal of Industrial Engineering, vol. 27, no. 2, pp. 206-217, 2016. doi: 10.7166/27-2-1327
  8. H. Afrisal, “Metode pengenalan tempat secara visual berbasis fitur CNN untuk navigasi robot di dalam gedung,” Jurnal Teknologi dan Sistem Komputer, vol. 7, no. 2, pp. 47-55, 2019. doi: 10.14710/jtsiskom.7.2.2019.47-55
  9. A. Kondakor, Z. Torcsvari, and A. Nagy, “A lane tracking algorithm based on image processing,” in 12th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, May 2018, pp. 39-44. doi: 10.1109/SACI.2018.8440975
  10. G. Ko, K.-H. Oh, and H.-S. Ahn, “Image-based lane tracking in quadcopter,” in 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), Santa Clara, USA, Jun. 2016, pp. 387-392. doi: 10.1109/ISIE.2016.7744921
  11. L. A. P. Sánchez, C. A. A. Moreno, and H. A. B. Daza, “Design and construction of a line follower robot guided by pixels values of a camera connected to an FPGA,” in 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA), Bogota, Colombia, Sept. 2015, pp. 1-5. doi: 10.1109/STSIVA.2015.7330453
  12. A. R. Chaidir, K. Anam, and G. A. Rahardi, “Lane tracking pada robot beroda holonomic menggunakan pengolahan citra,” ELKOMIKA, vol. 8, no. 1, pp. 69-79, 2020. doi: 10.26760/elkomika.v8i1.69
  13. E. Ramaraj and A. S. Rajan, “Median filter using open multiprocessing in agriculture,” in IEEE 10th International Conference on Signal Processing, Beijing, Beijing, China, Oct. 2010, pp. 42-45. doi: 10.1109/ICOSP.2010.5656718
  14. Z. Xu, X. Baojie, and W. Guoxin, “Canny edge detection based on OpenCV,” in 13th IEEE International Conference on Electronic Measurement & Instruments, Yangzhou, China, Oct. 2018, pp. 53-56. doi: 10.1109/icemi.2017.8265710
  15. Y. Takei, Y. Shimizu, K. Hirasawa, and H. Nanto, “Braitenberg's vehicle-like odor plume tracking robot,” in IEEE SENSORS, Valencia, Spain, Nov. 2014, pp. 1276-1279. doi: 10.1109/ICSENS.2014.6985243
  16. T. Salumäe, I. Rañó, O. Akanyeti, and M. Kruusmaa, “Against the flow: A Braitenberg controller for a fish robot,” in 2012 IEEE International Conference on Robotics and Automation, Saint Paul, USA, May 2012, pp. 4210-4215. doi: 10.1109/ICRA.2012.6225023

Last update:

  1. Early Warning System Design for Flood Disasters Using the IoT-Based Fuzzy Logic Control Method

    Gamma Aditya Rahardi, Wahyu Muldayani, Mochamad Diki Ari Wijaya, Dodi Setiabudi, Hasanur Mohammad Firdausi. 2022 International Conference on Electrical Engineering, Computer and Information Technology (ICEECIT), 2022. doi: 10.1109/ICEECIT55908.2022.10030237
  2. Autonomous car steering control and sign detection utilizing Haar Cascade and PID

    Mohammad Chasrun Hasani, Rochmat Jaya Putra, Novendra Setyawan. 1ST INTERNATIONAL CONFERENCE ON TECHNOLOGY, INFORMATICS, AND ENGINEERING, 2453 , 2022. doi: 10.1063/5.0094256

Last update: 2024-04-22 15:43:52

No citation recorded.