Intelligent Multi-Agent Robotics for Warehouse Automation and Resilient Supply Chain Infrastructure

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@article{1709767,
      author = {Umair Ejaz, S A Mohaiminul Islam, Ankur Sarkar, Aidar Imashev},
      title = {Intelligent Multi-Agent Robotics for Warehouse Automation and Resilient Supply Chain Infrastructure},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {5},
      pages = {258-276},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709767.pdf},
      abstract = {The growing level of complexity, pacing, and volatility of the global supply network requires smart, flexible, and decentralized automation technology. This paper will discuss how intelligent multi-agent robotic systems (MAS) in warehouses are being used as a revolutionary concept in maximizing the efficiency of operations in warehouses and resilience along the supply chain. Using distributed artificial intelligence, autonomous navigation, and decentralized control architectures, MAS enable the real-time coordination of various tasks, such as inventory tracking, order picking, goods transportation, and system optimization. As opposed to more conventional centralized systems, multi-agent systems are, by nature, scalable, fault-tolerant, and continuously working despite partial failures within the system or external attacks.
The paper provides a detailed review of the functioning of MAS in cooperative warehouse systems, paying particular attention to aspects such as communication between agents, task distribution algorithms, sensor integration, and adaptive learning. It also discusses the role that MAS plays in building resilient supply chain infrastructures by autonomously switching between routes, dynamically reconfiguring the system, and effectively handling all forms of disturbance. A data-based comparison table has been presented comparing the single-agent solutions with Alteon single-agent systems, which includes the performance data with a focus on important KPIs: throughput, response time, and recovery efficiency.
The other major issues associated with the deployment of MAS that are mentioned in the article are sluggishness in decision-making, cybersecurity threats, compatibility of hardware, and ethical issues. Lastly, it indicates some of the emerging trends like edge computing, swarm intelligence, and human-robot teaming, and predicts their implication for next-generation logistics systems. Dedicated to the practical application and strategic vision of the study, it provides an academically progressive blueprint of how to integrate intelligent robotics in warehousing and supply chain infrastructure, affecting those interested in academic research, industrial engineering, and supply chain innovation the same.},
      keywords = {Multi-Agent Systems, Warehouse Robotics, Intelligent Automation, Supply Chain Resilience, Collaborative Robotics (Cobots), Decentralized Decision-Making, AI-Driven Logistics},
      month = {November},
  }