Controlling the Mobile Robot with the Pure Pursuit Algorithm to Tracking the Reference Path Sent from the Android Device

Öz

Many of the equipment and machines we use in our everyday lives have changed due to major advancements in today's technology. Smartphones, which have made great progress especially in the last decade, perform many tasks in addition to interpersonal communication. Controlling robots, which are increasingly used in daily life and widely included in the literature, is one of these tasks. In this study, the pure pursuit algorithm was used to control the position of a non-holonomic differential drive mobile robot, and the path information to be tracked was received from an Android mobile device as a reference. An application design has been carried out for Android devices. The information for the path drawn here was transferred via the internet to a Google Spreadsheet. Coordinate information obtained from Google tables in MATLAB was separated as x and y axis information and entered into MATLAB/Simulink as waypoints of the pure pursuit algorithm and the position control of the robot was carried out. Error analysis was made by taking the differences between the reference path and the actual movement and the control performance was examined. Additionally, the effect of the approach distance value of the pure pursuit algorithm on the error is presented.

Anahtar Kelimeler

• Communication
• Mobile robot
• Android application
• Pure pursuit algorithm

References

1. [1] B. Tang, Z. Zhu, and J. Luo, “Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning,” International Journal of Advanced Robotic Systems, vol. 13, no. 3, p. 86, Jan. 2016, doi: https://doi.org/10.5772/63812.
2. [2] M. N. A. Wahab, S. Nefti-Meziani, and A. Atyabi, “A comparative review on mobile robot path planning: Classical or meta-heuristic methods” Annual Reviews in Control, Oct. 2020, doi: https://doi.org/ 10.1016/ j.arcontrol .2020 .10.001.
3. [3] S. Lin, A. Liu, J. Wang, and X. Kong, “A Review of Path-Planning Approaches for Multiple Mobile Robots,” Machines, vol. 10, no. 9, p. 773, Sep. 2022, doi: https://doi.org/10.3390/machines10090773.
4. [4] F. Gul, I. Mir, L. Abualigah, P. Sumari, and A. Forestiero, “A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions,” Electronics, vol. 10, no. 18, p. 2250, Sep. 2021, doi: https://doi.org/10.3390/electro nics10182250.
5. [5] C. Liu, J. Zhao, and N. Sun, “A Review of Collaborative Air-Ground Robots Research,” Journal of Intelligent and Robotic Systems, vol. 106, no. 3, Oct. 2022, doi: https://doi.org/10.1007/s10846-022-01756-4.
6. [6] S. Mellah, G. Graton, E. M. El Adel, M. Ouladsine and A. Planchais, "Actuator Health State Monitoring & Degradation Impact Study on a 4-Mecanum Wheeled Mobile Robot Behaviour," 2021 29th Mediterranean Conference on Control and Automation (MED), PUGLIA, Italy, 2021, pp. 1076-1081, doi: 10.1109/MED51440.2021.9480231.
7. [7] Z. Sun, H. Xie, J. Zheng, Z. Man, and D. He, “Path-following control of Mecanum-wheels omnidirectional mobile robots using nonsingular terminal sliding mode,” Mechanical Systems and Signal Processing, vol. 147, p. 107128, Jan. 2021, doi: https://doi.org/10.1016/j.ymssp.2020.107128.
8. [8] R. P. M. Chan, K. A. Stol, and C. R. Halkyard, “Review of modeling and control of two-wheeled robots,” Annual Reviews in Control, vol. 37, no. 1, pp. 89–103, Apr. 2013, doi: https://doi.org/10.1016/j.arcontrol.2013.03.004.

9. [9] S. Peng and W. Shi, "Adaptive Fuzzy Output Feedback Control of a Nonholonomic Wheeled Mobile Robot," in IEEE Access, vol. 6, pp. 43414-43424, 2018, doi: 10.1109/ACCESS.2018.2862163.
10. [10] M. Begnini, D. W. Bertol, and N. A. Martins, “A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results,” Control Engineering Practice, vol. 64, pp. 27–43, Jul. 2017, doi: https://doi.org/10.1016/j. conengprac. 2017.04.006.
11. [11] H. Zhao, C. Luo, Y. Xu, and J. Li, "Differential Steering Control for 6 × 6 Wheel-drive Mobile Robot," 2021 26th International Conference on Automation and Computing (ICAC), Portsmouth, United Kingdom, 2021, pp. 1-6, doi: 10.23919/ICAC50006.2021.9594210.
12. [12] P. Petrov and V. Georgieva, "Adaptive Velocity Control for a Differential Drive Mobile Robot," 2018 20th International Symposium on Electrical Apparatus and Technologies (SIELA), Bourgas, Bulgaria, 2018, pp. 1-4, doi: 10.1109/SIELA.2018.8447091.
13. [13] G. Klančar, A. Zdešar, and M. Krishnan, “Robot Navigation Based on Potential Field and Gradient Obtained by Bilinear Interpolation and a Grid-Based Search,” Sensors, vol. 22, no. 9, p. 3295, Apr. 2022, doi: https://doi.org/10.3390/s22093295.
14. [14] M. A. Contreras-Cruz, V. Ayala-Ramirez, and U. H. Hernandez-Belmonte, “Mobile robot path planning using artificial bee colony and evolutionary programming,” Applied Soft Computing, vol. 30, pp. 319–328, May 2015, doi: https://doi.org/10.1016/j .asoc. 2015.01.067.
15. [15] H. Qin, S. Shao, T. Wang, X. Yu, Y. Jiang, and Z. Cao, “Review of Autonomous Path Planning Algorithms for Mobile Robots,”, Drones, vol. 7, no. 3, pp. 211–211, 2023, doi:https://doi.org/10.3390/drones7030 21 1.
16. [16] S. K., Malu, & J. Majumdar,. “Kinematics, localization and control of differential drive mobile robot”. Global Journal of Research In Engineering, 14(1), 1-9. 2014
17. [17] M. Samuel, M. Maziah, M. Hussien, and N. Y. Godi, “Control of Autonomous Vehicle Using Path Tracking: A Review,” Advanced Science Letters, vol. 24, no. 6, pp. 3877–3879, Jun. 2018, doi: https://doi.org/10.1166/ asl. 2018.11502.
18. [18] S. Hong, “An Effıcıent Iot Applıcatıon Development Based On Iot Knowledge Modules,” Issues In Information Systems, 2020, doi: https://doi.org/10.48009/3_iis_2020_72-82.
19. [19] E. Pasternak, R. Fenichel, and A. N. Marshall, "Tips for creating a block language with blockly," 2017 IEEE Blocks and Beyond Workshop (B&B), Raleigh, NC, USA, 2017, pp. 21-24, doi: 10.1109/BLOCKS.2017.8120404.
20. [20] M. Aktaş, F. Polat, and M. Oflezer, “Bluetooth Ve Wifi Kontrollü Mobil Robot Tasarımı Ve Uygulaması”, İleri Teknoloji Bilimleri Dergisi, vol. 7, no. 3, pp. 29–35, 2018.
21. [21] R. K. Fahmidur, H. M. A. Munaim, S. M. Tanvir and A. S. Sayem, "Internet controlled robot: A simple approach," 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India, 2016, pp. 1190-1194, doi: 10.1109/ICEEOT.2016.7754873.
22. [22] P., Sıngporn, & S. Kamon, “Controlling the Line Follower Delivery Robot with MIT APP Inventor”. Journal of Technology and Innovation in Tertiary Education, 1(1), 9-16, 2018
23. [23] O. Bingöl, Ö. Aydoğan, B. Özkaya, N. Şen, “Android Cihaz ile Tekerlekli Sandalye Kontrolü”, Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Özel Sayı (164‐169). 2016
24. [24] M. Saravanan, B. Selvababu, A. Jayan, A. Anand, and A. Raj, “Arduino Based Voice Controlled Robot Vehicle,” IOP Conference Series: Materials Science and Engineering, vol. 993, p. 012125, Dec. 2020, doi: https://doi.org/10.1088/1757-899x/993/1/012125.
25. [25] Google Sheets features, Access Date: 01 January 2024 https://www.google.com/sheets/about/
26. [26] M. Samuel, M. Maziah, M. Hussien, and N. Y. Godi, “Control of Autonomous Vehicle Using Path Tracking: A Review,” Advanced Science Letters, vol. 24, no. 6, pp. 3877–3879, Jun. 2018, doi: https://doi.org/10.1166/asl. 2018.11502.
27. [27] G. GÜRGÜZE, & İ. TÜRKOĞLU, “Dinamik Modeli Bilinen Diferansiyel Mobil Robotun Pure Pursuit Algoritması İle Pozisyon Kontrolünün Yapılması”, International Congress on HumanComputer Interaction, Optimization and Robotic Applications, 2019
28. [28] -J. Wang, T. -M. Hsu and T. -S. Wu, " The improved pure pursuit algorithm for autonomous driving advanced system" 2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IWCIA), Hiroshima, Japan, 2017, pp. 33-38, doi: 10.1109/IWCIA.2017.8203557.