Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots

Oğuz Mısır; Muhammed Çelik; Levent Gökrem

doi:10.29137/umagd.1118039

TR EN

Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots

Abstract

In this paper, a waypoint-based path tracking approach is suggested for the swarm robots to follow the desired path in an organized way. In the study, the applicability of the waypoint-based path tracking on the swarm robots that show flexible and scalable behavior has been demonstrated. To evaluate the proposed path planing approach with regard to scalability and flexibility, simulations have been applied in with/without obstacle arenas with different numbers of robots and according to different lookahead distances. With the proposed approach, each swarm robots exhibit swarm behavior in an organized manner depending on the distance of the lookahead to the path to track in the with / without obstacle arenas.

Keywords

path planing, path tracking, swarm robotics, self-organizing, pure pursuit

References

Referans1 Bacha, S., Saadi, R., Ayad, M. Y., Aboubou, A., & Bahri, M. (2017). A review on vehicle modeling and control technics used for autonomous vehicle path following. International Conference on Green Energy and Conversion Systems, GECS 2017, 1–6. https://doi.org/10.1109/GECS.2017.8066221
Referans2 Bayindir, L. (2016). A review of swarm robotics tasks. Neurocomputing, 172, 292–321. https://doi.org/10.1016/j.neucom.2015.05.116
Referans3 Bayindir, L., & Şahin, E. (2007). A review of studies in swarm robotics. Turkish Journal of Electrical Engineering and Computer Sciences, 15(2), 115–147. http://dergipark.gov.tr/tbtkelektrik/issue/12085/144468
Referans4 Bibuli, M., Bruzzone, G., Caccia, M., Gasparri, A., Priolo, A., & Zereik, E. (2014). Swarm-based path-following for cooperative unmanned surface vehicles. Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 228(2), 192–207. https://doi.org/10.1177/1475090213516108
Referans5 Borenstein, J., & Koren, Y. (1989). Real-Time Obstacle Avoidance for Fast Mobile Robots. IEEE Transactions on Systems, Man and Cybernetics, 19(5), 1179–1187. https://doi.org/10.1109/21.44033
Referans6 Borenstein, J., & Koren, Y. (1991). The Vector Field Histogram—Fast Obstacle Avoidance for Mobile Robots. IEEE Transactions on Robotics and Automation, 7(3), 278–288. https://doi.org/10.1109/70.88137
Referans7 Buccieri, D., Perritaz, D., Mullhaupt, P., Jiang, Z. P., & Bonvin, D. (2009). Velocity-scheduling control for a unicycle mobile robot: Theory and experiments. IEEE Transactions on Robotics, 25(2), 451–458. https://doi.org/10.1109/TRO.2009.2014494
Referans8 Campion, G., Bastin, G., & D’Andréa-Novel, B. (1996). Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Transactions on Robotics and Automation, 12(1), 47–62. https://doi.org/10.1109/70.481750
Referans9 Chandrasekhar Rao, D., Kabat, M. R., Das, P. K., & Jena, P. K. (2018). Cooperative Navigation Planning of Multiple Mobile Robots Using Improved Krill Herd. Arabian Journal for Science and Engineering, 43(12), 7869–7891. https://doi.org/10.1007/s13369-018-3216-0
Referans10 Chen, Q., Wang, X., & Yang, J. (2018). Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method. Mathematical Problems in Engineering, 2018. https://doi.org/10.1155/2018/3104397

Referans11 Cibooglu, M., Karapinar, U., & Soylemez, M. T. (2017). Hybrid controller approach for an autonomous ground vehicle path tracking problem. 2017 25th Mediterranean Conference on Control and Automation, MED 2017, 583–588. https://doi.org/10.1109/MED.2017.7984180
Referans12 Craig Coulter, R. (1990). Implementation of Pure Pursuit Path Tracking Algorithm. Camegie Mellon University. es. Journal of Manufacturing Systems, 54(December 2019), 152–173. https://doi.org/10.1016/j.jmsy.2019.12.002
Referans13 Gong, Z., Xie, F., Liu, X. J., & Shentu, S. (2020). Obstacle-crossing Strategy and Formation Parameters Optimization of a Multi-tracked-mobile-robot System with a Parallel Manipulator. Mechanism and Machine Theory, 152, 103919. https://doi.org/10.1016/j.mechmachtheory.2020.103919
Referans14 Heinrich, M. K., Soorati, M. D., Kaiser, T. K., Wahby, M., & Hamann, H. (2019). Swarm robotics: Robustness, scalability, and self-X features in industrial applications. IT - Information Technology, 61(4), 159–167. https://doi.org/10.1515/itit-2019-0003
Referans15 Heo, S. N., Lu, S. Y., Shin, J. S., & Lee, H. H. (2018, November 27). Multi-Robot-Multi-Target Path Planning and Position Estimation for Disaster area. 2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018. https://doi.org/10.1109/ICT-ROBOT.2018.8549910
Referans16 Hoffmann, G. M., Tomlin, C. J., Montemerlo, M., & Thrun, S. (2007). Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing. Proceedings of the American Control Conference, 2296–2301. https://doi.org/10.1109/ACC.2007.4282788
Referans17 Horvath, E., Hajdu, C., & Koros, P. (2019). Novel Pure-Pursuit Trajectory Following Approaches and their Practical Applications. 10th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2019 - Proceedings, 597–602. https://doi.org/10.1109/CogInfoCom47531.2019.9089927
Referans18 Kim, D. H., Kim, C. J., & Han, C. S. (2010). Geometric path tracking and obstacle avoidance methods for an autonomous navigation of nonholonomic mobile robot. Journal of Institute of Control, Robotics and Systems, 16(8), 771–779. https://doi.org/10.5302/J.ICROS.2010.16.8.771
Referans19 Kim, J., & Kim, B. K. (2020). Cornering Trajectory Planning Avoiding Slip for Differential-Wheeled Mobile Robots. IEEE Transactions on Industrial Electronics, 67(8), 6698–6708. https://doi.org/10.1109/TIE.2019.2941156
Referans20 Lal, D. S., Vivek, A., & Selvaraj, G. (2018). Lateral control of an autonomous vehicle based on Pure Pursuit algorithm. Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy: Exploring Energy Solutions for an Intelligent Power Grid, TAP Energy 2017, 1–8. https://doi.org/10.1109/TAPENERGY.2017.8397361
Referans21 Lee, K., Jeon, S., Kim, H., & Kum, D. (2019). Optimal Path Tracking Control of Autonomous Vehicle: Adaptive Full-State Linear Quadratic Gaussian (LQG) Control. IEEE Access, 7, 109120–109133. https://doi.org/10.1109/ACCESS.2019.2933895
Referans22 Mısır, O., Gökrem, L., & Serhat Can, M. (2020). Fuzzy-based self organizing aggregation method for swarm robots. BioSystems, 196, 104187. https://doi.org/10.1016/j.biosystems.2020.104187
Referans23 Morales, J., Martínez, J. L., Martínez, M. A., & Mandow, A. (2009). Pure-pursuit reactive path tracking for nonholonomic mobile robots with a 2D laser scanner. Eurasip Journal on Advances in Signal Processing, 2009. https://doi.org/10.1155/2009/935237
Referans24 Morgansen, K. A., Triplett, B. I., & Klein, D. J. (2007). Geometric methods for modeling and control of free-swimming fin-actuated underwater vehicles. IEEE Transactions on Robotics, 23(6), 1184–1199. https://doi.org/10.1109/LED.2007.911625
Referans25 Ohta, H., Akai, N., Takeuchi, E., Kato, S., & Edahiro, M. (2016). Pure pursuit revisited: Field testing of autonomous vehicles in urban areas. Proceedings - 4th IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, CPSNA 2016, 7–12. https://doi.org/10.1109/CPSNA.2016.10
Referans26 Oliveira, T., Encarnacao, P., & Aguiar, A. P. (2013). Moving path following for autonomous robotic vehicles. 2013 European Control Conference, ECC 2013, 3320–3325. https://doi.org/10.23919/ecc.2013.6669459
Referans27 Oriolo, G., De Luca, A., & Vendittelli, M. (2002). WMR control via dynamic feedback linearization: Design, implementation, and experimental validation. IEEE Transactions on Control Systems Technology, 10(6), 835–852. https://doi.org/10.1109/TCST.2002.804116
Referans28 Park, H. G., Ahn, K. K., Park, M. K., & Lee, S. H. (2018). Study on Robust Lateral Controller for Differential GPS-Based Autonomous Vehicles. International Journal of Precision Engineering and Manufacturing, 19(3), 367–376. https://doi.org/10.1007/s12541-018-0044-9
Referans29 Park, M., Lee, S., & Han, W. (2015). Development of steering control system for autonomous vehicle using geometry-based path tracking algorithm. ETRI Journal, 37(3), 617–625. https://doi.org/10.4218/etrij.15.0114.0123
Referans30 Patle, B. K., Babu L, G., Pandey, A., Parhi, D. R. K., & Jagadeesh, A. (2019). A review: On path planning strategies for navigation of mobile robot. In Defence Technology (Vol. 15, Issue 4, pp. 582–606). China Ordnance Society. https://doi.org/10.1016/j.dt.2019.04.011
Referans31 Qu, P., Xue, J., Ma, L., & Ma, C. (2015). A constrained VFH algorithm for motion planning of autonomous vehicles. IEEE Intelligent Vehicles Symposium, Proceedings, 2015-Augus(Iv), 700–705. https://doi.org/10.1109/IVS.2015.7225766
Referans32 Saeed, R. A., Recupero, D. R., & Remagnino, P. (2020). A Boundary Node Method for path planning of mobile robots. Robotics and Autonomous Systems, 123, 103320. https://doi.org/10.1016/j.robot.2019.103320
Referans33 Shan, Y., Yang, W., Chen, C., Zhou, J., Zheng, L., & Li, B. (2015). CF-Pursuit: A Pursuit Method with a Clothoid Fitting and a Fuzzy Controller for Autonomous Vehicles. International Journal of Advanced Robotic Systems, 12(9). https://doi.org/10.5772/61391
Referans34 Snider, J. M. (2009). Automatic Steering Methods for Autonomous Automobile Path Tracking. In Work (Issue February).http://www.ri.cmu.edu/pub_files/2009/2/Automatic_Steering_Methods_for_Autonomous_Automobile_Path_Tracking.pdf
Referans35 Soysal, O., Bahçeci, E., & Şahin, E. (2007). Aggregation in Swarm Robotic Systems : Evolution and Probablistic Control. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 15(2), 199–225. http://dergipark.gov.tr/download/article-file/125895
Referans36 Survey, A. (2005). Local Navigation for Unmanned Ground. December.
Referans37 Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P., Strohband, S., Dupont, C., Jendrossek, L. E., Koelen, C., … Mahoney, P. (2006). Stanley: The robot that won the DARPA Grand Challenge. Journal of Field Robotics, 23(9), 661–692. https://doi.org/10.1002/rob.20147
Referans38 Wang, H., Liu, B., Ping, X., & An, Q. (2019). Path Tracking Control for Autonomous Vehicles Based on an Improved MPC. IEEE Access, 7, 161064–161073. https://doi.org/10.1109/ACCESS.2019.2944894
Referans39 Yaguchi, Y., & Tamagawa, K. (2020). A waypoint navigation method with collision avoidance using an artificial potential method on random priority. Artificial Life and Robotics, 25(2), 278–285. https://doi.org/10.1007/s10015-020-00583-w
Referans40 Yeu, T. K., Park, S. J., Hong, S., Kim, H. W., & Choi, J. S. (2006). Path tracking using vector pursuit algorithm for tracked vehicles driving on the soft cohesive soil. 2006 SICE-ICASE International Joint Conference, 2781–2786. https://doi.org/10.1109/SICE.2006.314707
Referans41 Yu, L., Yan, X., Kuang, Z., Chen, B., & Zhao, Y. (2020). Driverless bus path tracking based on fuzzy pure pursuit control with a front axle reference. Applied Sciences (Switzerland), 10(1). https://doi.org/10.3390/app10010230
Referans42 Zhang, W., Gai, J., Zhang, Z., Tang, L., Liao, Q., & Ding, Y. (2019). Double-DQN based path smoothing and tracking control method for robotic vehicle navigation. Computers and Electronics in Agriculture, 166, 104985. https://doi.org/10.1016/j.compag.2019.104985
Referans43 Zhao, H., Liu, H., Leung, Y. W., & Chu, X. (2018). Self-Adaptive Collective Motion of Swarm Robots. IEEE Transactions on Automation Science and Engineering, 15(4), 1533–1545. https://doi.org/10.1109/TASE.2018.2840828
Referans44 Zhou, H., Guvenc, L., & Liu, Z. (2017). Design and evaluation of path following controller based on MPC for autonomous vehicle. Chinese Control Conference, CCC, 9934–9939. https://doi.org/10.23919/ChiCC.2017.8028942

Details

Primary Language

English

Subjects

Electrical Engineering

Journal Section

Research Article

Authors

Oğuz Mısır
0000-0002-3785-1795
Türkiye

Muhammed Çelik
0000-0001-6909-7830
Türkiye

Levent Gökrem ^*
0000-0003-2101-5378
Türkiye

Publication Date

July 31, 2022

Submission Date

May 18, 2022

Acceptance Date

June 29, 2022

Published in Issue

Year 2022 Volume: 14 Number: 2

DOI

https://doi.org/10.29137/umagd.1118039

IZ

https://izlik.org/JA63MY29BP

APA

Mısır, O., Çelik, M., & Gökrem, L. (2022). Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots. International Journal of Engineering Research and Development, 14(2), 799-815. https://doi.org/10.29137/umagd.1118039

AMA

1.Mısır O, Çelik M, Gökrem L. Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots. IJERAD. 2022;14(2):799-815. doi:10.29137/umagd.1118039

Chicago

Mısır, Oğuz, Muhammed Çelik, and Levent Gökrem. 2022. “Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots”. International Journal of Engineering Research and Development 14 (2): 799-815. https://doi.org/10.29137/umagd.1118039.

EndNote

Mısır O, Çelik M, Gökrem L (July 1, 2022) Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots. International Journal of Engineering Research and Development 14 2 799–815.

IEEE

[1]O. Mısır, M. Çelik, and L. Gökrem, “Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots”, IJERAD, vol. 14, no. 2, pp. 799–815, July 2022, doi: 10.29137/umagd.1118039.

ISNAD

Mısır, Oğuz - Çelik, Muhammed - Gökrem, Levent. “Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots”. International Journal of Engineering Research and Development 14/2 (July 1, 2022): 799-815. https://doi.org/10.29137/umagd.1118039.

JAMA

1.Mısır O, Çelik M, Gökrem L. Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots. IJERAD. 2022;14:799–815.

MLA

Mısır, Oğuz, et al. “Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots”. International Journal of Engineering Research and Development, vol. 14, no. 2, July 2022, pp. 799-15, doi:10.29137/umagd.1118039.

Vancouver

1.Oğuz Mısır, Muhammed Çelik, Levent Gökrem. Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots. IJERAD. 2022 Jul. 1;14(2):799-815. doi:10.29137/umagd.1118039

Cited By

SÜRÜ ROBOTLARI İÇİN İŞ BİRLİĞİNE DAYALI YOL PLANLAMA VE ENGELDEN KAÇINMA ALGORİTMALARININ KARŞILAŞTIRMALI ANALİZİ

Mühendislik Bilimleri ve Tasarım Dergisi

https://doi.org/10.21923/jesd.1616072

Kırıkkale University, Faculty of Engineering and Natural Science, 71450 Yahşihan / Kırıkkale, Türkiye.

ijerad@kku.edu.tr