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

Year 2022, Volume: 14 Issue: 2, 799 - 815, 31.07.2022

Oğuz Mısır Muhammed Çelik Levent Gökrem

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

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