Main Article Content
Abstract
Traditional warehouse management systems face unprecedented challenges in the Industry 4.0 era, including escalating e-commerce demands, acute labor shortages, and critical requirements for real-time inventory visibility. Existing solutions fail to deliver the flexibility, scalability, and operational efficiency essential for contemporary supply chain operations. A novel integration framework combining Autonomous Mobile Robots (AMR) with Cyber-Physical Systems (CPS) is presented to enable intelligent, adaptive inventory management in smart warehouse environments. A multi-layered CPS architecture incorporating AMR fleet coordination, real-time data analytics, and digital twin synchronization is proposed. The framework employs distributed task allocation algorithms, dynamic path planning strategies, and predictive inventory optimization models. Implementation leverages edge computing for real-time decision-making and cloud infrastructure for comprehensive data analysis and storage. Experimental validation in industrial environments demonstrates significant performance improvements: 42% enhancement in order fulfillment speed, 35% reduction in inventory holding costs, and 89% accuracy in real-time stock tracking. The system maintained 99.2% uptime reliability while successfully managing 3× peak demand variations. The research advances smart logistics by establishing a scalable, generalizable CPS-AMR framework applicable across diverse warehouse environments. The findings provide actionable guidelines for Industry 4.0 transformation initiatives and establish theoretical foundations for next-generation autonomous warehouse systems.
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References
- G. Fragapane, R. De Koster, F. Sgarbossa, J.O. Strandhagen, Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda, European journal of operational research 294(2) (2021) 405-426. https://doi.org/10.1016/j.ejor.2021.01.019
- A.K. Grover, M.H. Ashraf, Leveraging autonomous mobile robots for Industry 4.0 warehouses: a multiple case study analysis, The International Journal of Logistics Management 35(4) (2023) 1168-1199. https://doi.org/10.1108/IJLM-09-2022-0362
- B. Cherniavskyi, H. Blakyta, V. Susidenko, A. Andreichenko, Y. Remyha, O. Podmazko, Innovative technologies and digital models in the post-war recovery of the transport and logistics system of Ukraine, ECONOMY IN THE ERA OF DIGITAL TRANSFORMATION: TRENDS, OPPORTUNITIES (2025) 110. DOI:10.21303/978-9908-9706-0-8.ch5
- S. Warita, K. Fujita, Online planning for autonomous mobile robots with different objectives in warehouse commissioning task, Information 15(3) (2024) 130. https://doi.org/10.3390/info15030130
- R. Keith, H.M. La, Review of autonomous mobile robots for the warehouse environment, arXiv preprint arXiv:2406.08333 (2024). https://doi.org/10.48550/arXiv.2406.08333
- S. Attaran, M. Attaran, B.G. Celik, Digital Twins and Industrial Internet of Things: Uncovering operational intelligence in industry 4.0, Decision analytics journal 10 (2024) 100398. https://doi.org/10.1016/j.dajour.2024.100398
- E. Badakhshan, D. Ivanov, Integrating digital twin and blockchain for responsive working capital management in supply chains facing financial disruptions, International Journal of Production Research (2025) 1-35. https://doi.org/10.1080/00207543.2025.2507112
- O. Mata, P. Ponce, C. Perez, M. Ramirez, B. Anthony, B. Russel, P. Apte, B. MacCleery, A. Molina, Digital twin designs with generative AI: crafting a comprehensive framework for manufacturing systems, Journal of Intelligent Manufacturing (2025) 1-24. https://doi.org/10.1007/s10845-025-02583-8
- J.K. Verma, V. Ranga, Multi-robot coordination analysis, taxonomy, challenges and future scope, Journal of intelligent & robotic systems 102(1) (2021) 10. https://doi.org/10.1007/s10846-021-01378-2
- R. Sioud, M. Bamoumen, N. Hamani, A Novel Model for Multi-robot Task Assignment in Smart Warehouses, International Conference on Innovative Intelligent Industrial Production and Logistics, Springer, 2024, pp. 343-353. https://doi.org/10.1007/978-3-031-80775-6_24
- K.O. Aina, H. Bagheri, D.I. Goldman, Fault-Tolerant Multi-Robot Coordination with Limited Sensing within Confined Environments, arXiv preprint arXiv:2505.15036 (2025). https://doi.org/10.48550/arXiv.2505.15036
- P. Reznik Nadiia, А. Demchenko Tetyana, А. Slatvinskyi Maksym, V. Kosmidailo Inna, M. Khodakyvskyy Volodymyr, V. Bugaychuk Vita, V. Valinkevych Nataliia, Current Trends and Sustainable Development of Warehouse Logistics, Islamic Sustainable Finance, Law and Innovation: Opportunities and Challenges, Springer2023, pp. 543-550. https://doi.org/10.1007/978-3-031-27860-0_50
- P. Li, Z. An, S. Abrar, L. Zhou, Large language models for multi-robot systems: A survey, arXiv preprint arXiv:2502.03814 (2025). https://doi.org/10.48550/arXiv.2502.03814
- A. Drissi Elbouzidi, A. Ait El Cadi, R. Pellerin, S. Lamouri, E. Tobon Valencia, M.-J. Bélanger, The role of AI in warehouse digital twins: Literature review, Applied sciences 13(11) (2023) 6746. https://doi.org/10.3390/app13116746
- D.L. Van Bossuyt, D. Allaire, J.F. Bickford, T.A. Bozada, W. Chen, R.P. Cutitta, R. Cuzner, K. Fletcher, R. Giachetti, B. Hale, The Future of Digital Twin Research and Development, Journal of Computing and Information Science in Engineering 25(8) (2025) 080801. https://doi.org/10.1115/1.4068082
- C. SZCZUKA, M. BRUCHHAUSEN, Technical support to define performance and durability minimum requirements for industrial batteries, (2025). https://data.europa.eu/doi/10.2760/0701373
- K. Sharma, R. Doriya, Coordination of multi-robot path planning for warehouse application using smart approach for identifying destinations, Intelligent Service Robotics 14(2) (2021) 313-325. https://doi.org/10.1007/s11370-021-00363-w
- A.A. Tubis, J. Rohman, Intelligent warehouse in industry 4.0—systematic literature review, Sensors 23(8) (2023) 4105. https://doi.org/10.3390/s23084105
- R.K. Rainer Jr, R.G. Richey Jr, S. Chowdhury, How robotics is shaping digital logistics and supply chain management: An ongoing call for research, Journal of Business Logistics 46(1) (2025) e70005. DOI:10.1111/jbl.70005
- Y. Zhang, M.C. Fontaine, V. Bhatt, S. Nikolaidis, J. Li, Multi-robot coordination and layout design for automated warehousing, Proceedings of the International Symposium on Combinatorial Search, 2024, pp. 305-306. DOI:https://doi.org/10.1609/socs.v17i1.31593
- Vamsi Krishna Yarlagadda. Cutting-edge developments in Robotics for Smart Warehousing and Logistics Optimization. Robotics Xplore: USA Automation Digest, 2024, 1 (1), pp.61-79. ⟨hal-04787280⟩.
- Sattarov A. Warehouse Automation and Materials Handling: An Emerging Industry, Its Market Impact, and the Forces Challenging Its Growth. Journal of Data Analysis and Information Processing. 2025 Apr 11;13(2):199-212. DOI: 10.4236/jdaip.2025.132012
- K.F.E. Tsang, Y. Ni, C.F.R. Wong, L. Shi, A novel warehouse multi-robot automation system with semi-complete and computationally efficient path planning and adaptive genetic task allocation algorithms, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, 2018, pp. 1671-1676. DOI: 10.1109/ICARCV.2018.8581092
- M. Singh, R. Srivastava, E. Fuenmayor, V. Kuts, Y. Qiao, N. Murray, D. Devine, Applications of digital twin across industries: A review, Applied Sciences 12(11) (2022) 5727. https://doi.org/10.3390/app12115727
- P. Stavropoulos, Digital Twins of Manufacturing Processes Under Industry 5.0, Advances in Artificial Intelligence in Manufacturing II: Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, October 16, 2024, Athens, Greece, Springer Nature, 2025, p. 3. https://doi.org/10.1007/978-3-031-86489-6_1
References
G. Fragapane, R. De Koster, F. Sgarbossa, J.O. Strandhagen, Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda, European journal of operational research 294(2) (2021) 405-426. https://doi.org/10.1016/j.ejor.2021.01.019
A.K. Grover, M.H. Ashraf, Leveraging autonomous mobile robots for Industry 4.0 warehouses: a multiple case study analysis, The International Journal of Logistics Management 35(4) (2023) 1168-1199. https://doi.org/10.1108/IJLM-09-2022-0362
B. Cherniavskyi, H. Blakyta, V. Susidenko, A. Andreichenko, Y. Remyha, O. Podmazko, Innovative technologies and digital models in the post-war recovery of the transport and logistics system of Ukraine, ECONOMY IN THE ERA OF DIGITAL TRANSFORMATION: TRENDS, OPPORTUNITIES (2025) 110. DOI:10.21303/978-9908-9706-0-8.ch5
S. Warita, K. Fujita, Online planning for autonomous mobile robots with different objectives in warehouse commissioning task, Information 15(3) (2024) 130. https://doi.org/10.3390/info15030130
R. Keith, H.M. La, Review of autonomous mobile robots for the warehouse environment, arXiv preprint arXiv:2406.08333 (2024). https://doi.org/10.48550/arXiv.2406.08333
S. Attaran, M. Attaran, B.G. Celik, Digital Twins and Industrial Internet of Things: Uncovering operational intelligence in industry 4.0, Decision analytics journal 10 (2024) 100398. https://doi.org/10.1016/j.dajour.2024.100398
E. Badakhshan, D. Ivanov, Integrating digital twin and blockchain for responsive working capital management in supply chains facing financial disruptions, International Journal of Production Research (2025) 1-35. https://doi.org/10.1080/00207543.2025.2507112
O. Mata, P. Ponce, C. Perez, M. Ramirez, B. Anthony, B. Russel, P. Apte, B. MacCleery, A. Molina, Digital twin designs with generative AI: crafting a comprehensive framework for manufacturing systems, Journal of Intelligent Manufacturing (2025) 1-24. https://doi.org/10.1007/s10845-025-02583-8
J.K. Verma, V. Ranga, Multi-robot coordination analysis, taxonomy, challenges and future scope, Journal of intelligent & robotic systems 102(1) (2021) 10. https://doi.org/10.1007/s10846-021-01378-2
R. Sioud, M. Bamoumen, N. Hamani, A Novel Model for Multi-robot Task Assignment in Smart Warehouses, International Conference on Innovative Intelligent Industrial Production and Logistics, Springer, 2024, pp. 343-353. https://doi.org/10.1007/978-3-031-80775-6_24
K.O. Aina, H. Bagheri, D.I. Goldman, Fault-Tolerant Multi-Robot Coordination with Limited Sensing within Confined Environments, arXiv preprint arXiv:2505.15036 (2025). https://doi.org/10.48550/arXiv.2505.15036
P. Reznik Nadiia, А. Demchenko Tetyana, А. Slatvinskyi Maksym, V. Kosmidailo Inna, M. Khodakyvskyy Volodymyr, V. Bugaychuk Vita, V. Valinkevych Nataliia, Current Trends and Sustainable Development of Warehouse Logistics, Islamic Sustainable Finance, Law and Innovation: Opportunities and Challenges, Springer2023, pp. 543-550. https://doi.org/10.1007/978-3-031-27860-0_50
P. Li, Z. An, S. Abrar, L. Zhou, Large language models for multi-robot systems: A survey, arXiv preprint arXiv:2502.03814 (2025). https://doi.org/10.48550/arXiv.2502.03814
A. Drissi Elbouzidi, A. Ait El Cadi, R. Pellerin, S. Lamouri, E. Tobon Valencia, M.-J. Bélanger, The role of AI in warehouse digital twins: Literature review, Applied sciences 13(11) (2023) 6746. https://doi.org/10.3390/app13116746
D.L. Van Bossuyt, D. Allaire, J.F. Bickford, T.A. Bozada, W. Chen, R.P. Cutitta, R. Cuzner, K. Fletcher, R. Giachetti, B. Hale, The Future of Digital Twin Research and Development, Journal of Computing and Information Science in Engineering 25(8) (2025) 080801. https://doi.org/10.1115/1.4068082
C. SZCZUKA, M. BRUCHHAUSEN, Technical support to define performance and durability minimum requirements for industrial batteries, (2025). https://data.europa.eu/doi/10.2760/0701373
K. Sharma, R. Doriya, Coordination of multi-robot path planning for warehouse application using smart approach for identifying destinations, Intelligent Service Robotics 14(2) (2021) 313-325. https://doi.org/10.1007/s11370-021-00363-w
A.A. Tubis, J. Rohman, Intelligent warehouse in industry 4.0—systematic literature review, Sensors 23(8) (2023) 4105. https://doi.org/10.3390/s23084105
R.K. Rainer Jr, R.G. Richey Jr, S. Chowdhury, How robotics is shaping digital logistics and supply chain management: An ongoing call for research, Journal of Business Logistics 46(1) (2025) e70005. DOI:10.1111/jbl.70005
Y. Zhang, M.C. Fontaine, V. Bhatt, S. Nikolaidis, J. Li, Multi-robot coordination and layout design for automated warehousing, Proceedings of the International Symposium on Combinatorial Search, 2024, pp. 305-306. DOI:https://doi.org/10.1609/socs.v17i1.31593
Vamsi Krishna Yarlagadda. Cutting-edge developments in Robotics for Smart Warehousing and Logistics Optimization. Robotics Xplore: USA Automation Digest, 2024, 1 (1), pp.61-79. ⟨hal-04787280⟩.
Sattarov A. Warehouse Automation and Materials Handling: An Emerging Industry, Its Market Impact, and the Forces Challenging Its Growth. Journal of Data Analysis and Information Processing. 2025 Apr 11;13(2):199-212. DOI: 10.4236/jdaip.2025.132012
K.F.E. Tsang, Y. Ni, C.F.R. Wong, L. Shi, A novel warehouse multi-robot automation system with semi-complete and computationally efficient path planning and adaptive genetic task allocation algorithms, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, 2018, pp. 1671-1676. DOI: 10.1109/ICARCV.2018.8581092
M. Singh, R. Srivastava, E. Fuenmayor, V. Kuts, Y. Qiao, N. Murray, D. Devine, Applications of digital twin across industries: A review, Applied Sciences 12(11) (2022) 5727. https://doi.org/10.3390/app12115727
P. Stavropoulos, Digital Twins of Manufacturing Processes Under Industry 5.0, Advances in Artificial Intelligence in Manufacturing II: Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, October 16, 2024, Athens, Greece, Springer Nature, 2025, p. 3. https://doi.org/10.1007/978-3-031-86489-6_1