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Advancements in Cooperative Mobile Robots Control Strategies for Large-Scale Material Transport: Review
Corresponding Author(s) : Hendi Wicaksono Agung
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control,
Vol. 9, No. 4, November 2024
Abstract
This paper explores groundbreaking advancements in control strategies for cooperative mobile robots used in large-scale material transport, a critical aspect of modern industrial, manufacturing, logistics, and construction sectors. It delves into the development of sophisticated systems that enable seamless coordination among multiple mobile robot systems. The research presents a novel hierarchical finite state automaton for dynamic mission adaptation and a null space-based control scheme for precise task execution and enhanced system resilience. The introduction of Mecanum wheels facilitates flexible movement and manipulation of materials, thereby increasing the operational efficiency and safety. Cutting-edge sensory technology, including LiDAR (Light Detection and Ranging), and the implementation of Robot Operating System are highlighted for their roles in enhancing autonomous navigation and intelligent operation. Additionally, the paper discusses the impact of centralized and decentralized control methods in ensuring safe cooperative object transport. The findings contribute to the vision of Industry 4.0 by promoting the integration of automation and robotic cooperation in complex environments and present a foundational blueprint for further research. Challenges for future work such as scalability, communication efficiency, collision avoidance, and energy efficiency are also considered, underscoring the need for ongoing development of robust and scalable robotic systems to address modern transport challenges.
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- K. Okuhata, S. Ino, Y. Mizobuchi, G. Yang, S. Wang, and H. Okamura, “Development of Autonomous Material Transportation Robots: Mechanical Design and Safety Measurements,” in 2021 IEEE International Conference on Intelligence and Safety for Robotics (ISR), Mar. 2021, pp. 125–126. https://doi.org/10.1109/ISR50024.2021.9419531
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- L. Dong, Y. Chen, and X. Qu, “Formation Control Strategy for Nonholonomic Intelligent Vehicles Based on Virtual Structure and Consensus Approach,” Procedia Eng., vol. 137, pp. 415–424, 2016. https://doi.org/10.1016/j.proeng.2016.01.276
- Y. Liu, J. Gao, C. Liu, F. Zhao, and J. Zhao, “Reconfigurable Formation Control of Multi-Agents Using Virtual Linkage Approach,” Appl. Sci., vol. 8, no. 7, p. 1109, Jul. 2018. https://doi.org/10.3390/app8071109
- M. R. Mohamad Sapiee and K. A. Mohd Annuar, “Synchronous Mobile Robots Formation Control,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 16, no. 3, p. 1183, Jun. 2018. http://doi.org/10.12928/telkomnika.v16i3.8397
- Z. Zhang and J. Huang, “Behavioral Formation Control of Multiple Mecanum-wheeled Mobile Manipulators,” in 2020 IEEE 16th International Conference on Control & Automation (ICCA), Oct. 2020, pp. 642–647. https://doi.org/10.1109/ICCA51439.2020.9264349
References
K. Okuhata, S. Ino, Y. Mizobuchi, G. Yang, S. Wang, and H. Okamura, “Development of Autonomous Material Transportation Robots: Mechanical Design and Safety Measurements,” in 2021 IEEE International Conference on Intelligence and Safety for Robotics (ISR), Mar. 2021, pp. 125–126. https://doi.org/10.1109/ISR50024.2021.9419531
M. Javaid, A. Haleem, R. P. Singh, and R. Suman, “Substantial capabilities of robotics in enhancing industry 4.0 implementation,” Cogn. Robot., vol. 1, no. May, pp. 58–75, 2021. https://doi.org/10.1016/j.cogr.2021.06.001
D. Bechtsis, N. Tsolakis, M. Vouzas, and D. Vlachos, Industry 4.0: Sustainable material handling processes in industrial environments, vol. 40. Elsevier Masson SAS, 2017. https://doi.org/10.1016/B978-0-444-63965-3.50382-2
J. Flayfel, G. Demesure, and H. B. El-Haouzi, “Contribution of the Omnidirectional Autonomous Mobile Robot to Manufacturing Systems Agility,” 2022, pp. 429–440. https://doi.org/10.1007/978-3-030-99108-1_31
S. Madhankumar, P. Anandraj, A. Varadarajan, R. A. Kumar, and K. Kaleeswaran, “Design and Modelling of Autonomous Mobile Robot for Material Handling,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Mar. 2021, pp. 738–742. https://doi.org/10.1109/ICACCS51430.2021.9441831
J. A. Marvel, R. Bostelman, and J. Falco, “Multi-Robot Assembly Strategies and Metrics,” ACM Comput. Surv., vol. 51, no. 1, pp. 1–32, Jan. 2019. https://doi.org/10.1145/3150225
C. C. Loh and A. Traechtler, “Cooperative Transportation of Aload Using Nonholonomic Mobile Robots,” Procedia Eng., vol. 41, pp. 860–866, 2012. https://doi.org/10.1016/j.proeng.2012.07.255
P. Paniagua-Contro et al., “Extension of Leader-Follower Behaviours for Wheeled Mobile Robots in Multirobot Coordination,” Math. Probl. Eng., vol. 2019, pp. 1–16, Apr. 2019. https://doi.org/10.1155/2019/4957259
E. Tuci, M. H. M. Alkilabi, and O. Akanyeti, “Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art,” Front. Robot. AI, vol. 5, May 2018. https://doi.org/10.3389/frobt.2018.00059
H. Farivarnejad and S. Berman, “Multirobot Control Strategies for Collective Transport,” Annu. Rev. Control. Robot. Auton. Syst., vol. 5, no. 1, pp. 205–219, May 2022. https://doi.org/10.1146/annurev-control-042920-095844
X. An, C. Wu, Y. Lin, M. Lin, T. Yoshinaga, and Y. Ji, “Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges,” IEEE Open J. Comput. Soc., vol. 4, pp. 23–36, 2023. https://doi.org/10.1109/OJCS.2023.3238324
M. Kassawat, E. Cervera, and A. P. del Pobil, “An Omnidirectional Platform for Education and Research in Cooperative Robotics,” Electronics, vol. 11, no. 3, p. 499, Feb. 2022. https://doi.org/10.3390/electronics11030499
L. Escobar, C. Moyano, G. Aguirre, G. Guerra, L. Allauca, and D. Loza, “Multi-Robot platform with features of Cyber-physical systems for education applications,” in 2020 IEEE ANDESCON, Oct. 2020, pp. 1–6. https://doi.org/10.1109/ANDESCON50619.2020.9272030
U. Dziomin, A. Kabysh, R. Stetter, and V. Golovko, “A Multi-Agent Reinforcement Learning Approach for the Efficient Control of Mobile Robots,” in Advances in Intelligent Robotics and Collaborative Automation, New York: River Publishers, 2022, pp. 123–145. https://www.doi.org/10.1201/9781003337119-6
T. Jiang, S. Zhang, R. Wang, and S. Wang, “Development and Verification of an Autonomous and Controllable Mobile Robot Platform,” Mechatronics Intell. Transp. Syst., vol. 2, no. 1, Mar. 2023. https://doi.org/10.56578/mits020102
J. Wu, C. Lv, L. Zhao, R. Li, and G. Wang, “Design and implementation of an omnidirectional mobile robot platform with unified I/O interfaces,” 2017 IEEE Int. Conf. Mechatronics Autom. ICMA 2017, pp. 410–415, 2017. https://doi.org/10.1109/ICMA.2017.8015852
C. Fan, F. Zeng, S. Shirafuji, and J. Ota, “Development of a Three-Mobile-Robot System for Cooperative Transportation,” J. Mech. Robot., vol. 16, no. 2, Feb. 2024. https://doi.org/10.1115/1.4056771
J. Hu, P. Bhowmick, and A. Lanzon, “Group Coordinated Control of Networked Mobile Robots With Applications to Object Transportation,” IEEE Trans. Veh. Technol., vol. 70, no. 8, pp. 8269–8274, Aug. 2021. https://doi.org/10.1109/TVT.2021.3093157
H. Ebel, W. Luo, F. Yu, Q. Tang, and P. Eberhard, “Design and Experimental Validation of a Distributed Cooperative Transportation Scheme,” IEEE Trans. Autom. Sci. Eng., vol. 18, no. 3, pp. 1157–1169, Jul. 2021. https://doi.org/10.1109/TASE.2020.2997411
C. Beltrán, A. Cabrera, G. Delgado, and D. Iturralde, “Centralized Trajectory Tracking Controller for a Multi-robot System,” 2020, pp. 331–345. https://doi.org/10.1007/978-3-030-42531-9_27
M. Geng, K. Xu, X. Zhou, B. Ding, H. Wang, and L. Zhang, “Learning to Cooperate via an Attention-Based Communication Neural Network in Decentralized Multi-Robot Exploration,” Entropy, vol. 21, no. 3, p. 294, Mar. 2019. https://doi.org/10.3390/e21030294
P. Verma, P. Dasgupta, and C. Chakraborty, “A novel hybrid centralised decentralised framework for electric vehicles coordination,” IET Smart Grid, vol. 7, no. 1, pp. 89–100, Feb. 2024. https://doi.org/10.1049/stg2.12144
J.-Y. Jhang, C.-J. Lin, and K.-Y. Young, “Cooperative Carrying Control for Multi-Evolutionary Mobile Robots in Unknown Environments,” Electronics, vol. 8, no. 3, p. 298, Mar. 2019. https://doi.org/10.3390/electronics8030298
G. Wang, C. Wang, Q. Du, L. Li, and W. Dong, “Distributed Cooperative Control of Multiple Nonholonomic Mobile Robots,” J. Intell. Robot. Syst., vol. 83, no. 3–4, pp. 525–541, Sep. 2016. https://doi.org/10.1007/s10846-015-0316-x
A. Burghardt, P. Gierlak, and W. Skwarek, “Modeling of dynamics of cooperating wheeled mobile robots,” J. Theor. Appl. Mech., pp. 649–659, Sep. 2021. https://doi.org/10.15632/jtam-pl/141668
L. Zhang, Y. Sun, A. Barth, and O. Ma, “Decentralized Control of Multi-Robot System in Cooperative Object Transportation Using Deep Reinforcement Learning,” IEEE Access, vol. 8, pp. 184109–184119, 2020. https://doi.org/10.1109/ACCESS.2020.3025287
L. Dong, Y. Chen, and X. Qu, “Formation Control Strategy for Nonholonomic Intelligent Vehicles Based on Virtual Structure and Consensus Approach,” Procedia Eng., vol. 137, pp. 415–424, 2016. https://doi.org/10.1016/j.proeng.2016.01.276
Y. Liu, J. Gao, C. Liu, F. Zhao, and J. Zhao, “Reconfigurable Formation Control of Multi-Agents Using Virtual Linkage Approach,” Appl. Sci., vol. 8, no. 7, p. 1109, Jul. 2018. https://doi.org/10.3390/app8071109
M. R. Mohamad Sapiee and K. A. Mohd Annuar, “Synchronous Mobile Robots Formation Control,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 16, no. 3, p. 1183, Jun. 2018. http://doi.org/10.12928/telkomnika.v16i3.8397
Z. Zhang and J. Huang, “Behavioral Formation Control of Multiple Mecanum-wheeled Mobile Manipulators,” in 2020 IEEE 16th International Conference on Control & Automation (ICCA), Oct. 2020, pp. 642–647. https://doi.org/10.1109/ICCA51439.2020.9264349