Integrating Robotics in Modern Warehouse Logistics
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DOI:
https://doi.org/10.67228/30715628/IJMIET-2020PII8T1FPublished 12-04-2020
Warehouse Automation, Robotics, Autonomous Mobile Robots, Logistics Optimization, Smart Warehouses, Industry 4.0 Issue
Section
ArticlesHow to Cite
[1]B. K, “Integrating Robotics in Modern Warehouse Logistics”, ijmiet, vol. 3, no. 2, pp. 01–12, Dec. 2020, doi: 10.67228/30715628/IJMIET-2020PII8T1F.Abstract
Warehouse logistics has been fundamentally changed by the blistering development of e-commerce, global supply chains and consumer demands to be delivery in less time. Manual and semi-manual warehouse systems are gradually becoming incapable of satisfying contemporary requirements with respect to speed, accuracy, scale, and lowering operating costs. Consequently, robotics has become an important enabling technology of the next-generation warehouse. This paper will provide an in-depth analysis of integrating robotics into the operations of the contemporary warehouse logistics setting as seen through the architecture, operational processes, operational performance, and challenges in implementation. The paper discusses the different categories of warehouse robots, such as: autonomous mobile robots (AMRs), automated guided vehicles (AGVs), robotic picking of goods and collaborative robots (cobots). An extensive literature review underscores current developments, algorithm methods and industrial implementations. The suggested methodology presents a warehouse architecture based on modular robots that incorporates a perception system, a navigation system, a task allocation system and a fleet management system. Measures of performance evaluation including throughput, accuracy of order fulfillment, energy and operational cost are evaluated. The findings reveal a high level of productivity, scalability as well as reliability over traditional systems. The paper will end with the suggestions of research directions on how to continue with it in future, as the approaches of artificial intelligence, digital twins, and human/robot collaboration have been identified as the primary catalysts of intelligent warehouse ecosystems.
References
[1] Wurman, P. R., D’Andrea, R., & Mountz, M. (2008). Coordinating hundreds of cooperative, autonomous vehicles in warehouses. AI Magazine, 29(1), 9–20.
[2] D’Andrea, R. (2012). Guest editorial: A revolution in the warehouse: A retrospective on Kiva systems and the grand challenges ahead. IEEE Transactions on Automation Science and Engineering, 9(4), 638–639.
[3] Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic Robotics. MIT Press.
[4] Bonin-Font, F., Ortiz, A., & Oliver, G. (2008). Visual navigation for mobile robots: A survey. Journal of Intelligent and Robotic Systems, 53(3), 263–296.
[5] Kober, J., Bagnell, J. A., & Peters, J. (2013). Reinforcement learning in robotics: A survey. The International Journal of Robotics Research, 32(11), 1238–1274.
[6] Correll, N., et al. (2018). Analysis and observations from the Amazon Picking Challenge. IEEE Transactions on Automation Science and Engineering, 15(1), 172–188.
[7] Redmon, J., & Farhadi, A. (2018). YOLOv3: An incremental improvement. arXiv preprint arXiv:1804.02767.
[8] Krug, R., Stoyanov, T., Tincani, V., et al. (2016). The next step in robot commissioning: Autonomous picking and manipulation. IEEE Robotics & Automation Magazine, 23(3), 73–84.
[9] Gerkey, B. P., & Mataric, M. J. (2004). A formal analysis and taxonomy of task allocation in multi-robot systems. The International Journal of Robotics Research, 23(9), 939–954.
[10] Dias, M. B., Zlot, R., Kalra, N., & Stentz, A. (2006). Market-based multirobot coordination: A survey and analysis. Proceedings of the IEEE, 94(7), 1257–1270.
[11] Liu, C., Kroll, A., & Zhang, J. (2019). Multi-robot task allocation and path planning based on reinforcement learning. Robotics and Autonomous Systems, 118, 173–185.
[12] Boysen, N., de Koster, R., & Weidinger, F. (2019). Warehousing in the e-commerce era: A survey. European Journal of Operational Research, 277(2), 396–411.
[13] ISO 3691-4. (2020). Industrial trucks — Safety requirements and verification — Part 4: Driverless industrial trucks and their systems. International Organization for Standardization.
[14] Lasota, P. A., Fong, T., & Shah, J. A. (2017). A survey of methods for safe human–robot interaction. Foundations and Trends® in Robotics, 5(4), 261–349.
[15] Villani, V., Pini, F., Leali, F., & Secchi, C. (2018). Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications. Mechatronics, 55, 248–266.
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How to Cite
[1]B. K, “Integrating Robotics in Modern Warehouse Logistics”, ijmiet, vol. 3, no. 2, pp. 01–12, Dec. 2020, doi: 10.67228/30715628/IJMIET-2020PII8T1F.
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