ХНУРЕ Харківський національний університет радіоелектроніки

Конференція MC&FPGA

Мова:

Algorithm for Finding the Optimal Way to Move a Mobile Platform Among Indefinite Obstacles

DOI: 10.35598/mcfpga.2022.007

Algorithm for Finding the Optimal Way to Move a Mobile Platform Among Indefinite Obstacles
Sergiy Novoselov, Oksana Sychova, Serhii Tesliuk

IV International Scientific and Practical Conference Theoretical and Applied Aspects of Device Development on Microcontrollers and FPGAs (MC&FPGA-2022), Kharkiv, Ukraine, 2022, pp. 21-23.

Date of Conference: 23–24 June 2022

Abstract
Abstract. The paper describes a method for determining the trajectory of a mobile robot inside a production room among obstacles. To determine the path of movement, a navigation system is used, which determines the robot’s own coordinates, plans the trajectory at the current time and controls its movement. A software tool for modeling the behavior of a mobile robot taking into account the properties of its mechatronic platform is proposed. The model of the adaptive control system of the mobile platform is described. The block diagram of the program for modeling the method of finding the optimal way to move a mobile platform among uncertain obstacles is considered. The simulation results are given.

Keywords: mobile robot, navigation system, optimal way, model, program.

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References

  1. Caruso D., Engel J., CremersD. Large-scale direct slam for omnidirectional cameras //2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 28 – October 2. 2015, Hamburg. Germany. – Hamburg, 2015.-P. 141-148.
  2. Теслюк С.І. Аналіз методів локалізації рухомого об’єкта у виробничих приміщеннях / С.І. Теслюк, Д.В. Мамонько / Матеріали конференції «Автоматизаці., електроніка та робототехніка. Стратегії розвитку та інноваційні технології».  2019. – С. 10-13.
  3. Мамонько Д.В. Розробка програмного для забезпечення керування траєкторією руху мобільної платформи / Збірник студентських наукових статей «Automation and Developed of Electronic Devices» АDED-2020. – 2020. – № 1. – С. 112-117.
  4. ORB-SLAM2 for Monocular, Stereo and RGB-D Cameras [Електронний ресурс]. – Електрон. текстові дані. – Режим доступу: https://webdiis.unizar.es/~raulmur/orbslam/
  5. Rituerto A. Visual SLAM with an omnidirectional camera // 2010 20th International Conference on Pattern Recognition CPR2010, 23-26 August 2010, Istanbul. Turkey: Proceedings. – Istanbul, 2010. – P. 348-351.
  6. Nevludov, O. Sychova, A. Andrusevich, S. Novoselov, D. Mospan and V. Mospan, “Simulation of the Sensor Network of Base Stations in a Local Positioning System in Intelligent Industries,” 2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP), Kremenchuk, Ukraine, 2020, pp. 1-6.
  7. S. Novoselov, O. Donskov, “Distributed Local Positioning System Using DWM1000 Location Chip,” 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, 2017,  pp. 489-492.
  8. S. P. Novoselov, O. N. Donskov, “Study of Mobile Device Wireless Control Technology in the Visible Range of the Electromagnetic Radiation,” Third International Scientific-Practical Conference Problems of Infocommunications Science and Technology (PIC S &T), Kharkiv, 2016, pp. 123-124.
  9. S. Novoselov, O. Sychova and S. Tesliuk, “Development of the Method Local Navigation of Mobile Robot a Based on the Tags with QR Code and Wireless Sensor Network,” 2019 IEEE XVth International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH), Polyana, Ukraine, 2019, pp. 46-51.
  10. I. Nevludov, O. Sychova, O. Reznichenko, S. Novoselov, D. Mospan and V. Mospan, “Control System for Agricultural Robot Based on ROS,” 2021 IEEE International Conference on Modern Electrical and Energy Systems (MEES), 2021, pp. 1-6, doi: 10.1109/MEES52427.2021.9598560.
  11. H. Pu, H. Wang, X. Liu, Z. Yu and K. Peng, “A high-precision absolute angular position sensor with Vernier capacitive arrays based on time grating”, IEEE Sensors J., vol. 19, no. 19, pp. 8626-8634, Oct. 2019.
  12. Zhang, S., Wang, S., Jing, F., Tan, M. (2019), “A Sensorless Hand Guiding Scheme Based on Model Identification and Control for Industrial Robot”, IEEE Transactions on Industrial Informatics, Vol. 15, No. 9, P. 5204–5213. DOI: https://doi.org/10.1109/ TII.2019.2900119.
  13. Roveda, L. (2019), “Adaptive Interaction Controller for Compliant Robot Base Applications”, IEEE Access, Vol. 7, P. 6553–6561. DOI: https://doi.org/10.1109/ACCESS.2018.2889849.
  14. Lai, R., Lin, W., Wu, Y. (2018), “Review of Research on the Key Technologies Application Fields and Development Trends of Intelligent Robots”, International Conference on Intelligent Robotics and Applications.
  15. Goel, R., Gupta, P. (2019), “Robotics and industry 4.0″ in A Roadmap to Industry 4.0”, Smart Production Sharp Business and Sustainable Development, Cham, Switzerland: Springer, P. 157–169, available at : https://www.springer.com/ gp/book/9783030145439.