inis 18(15): e2

Research Article

Distributed Optimization Framework for Industry 4.0 Automated Warehouses

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  • @ARTICLE{10.4108/eai.27-6-2018.155237,
        author={Ajay Kattepur and Hemant Kumar Rath and Arijit Mukherjee and Anantha Simha},
        title={Distributed Optimization Framework for Industry 4.0 Automated Warehouses},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        keywords={Industry 4.0, Intelligent Robotic Agent, Distributed Optimization, Warehouse Automation},
  • Ajay Kattepur
    Hemant Kumar Rath
    Arijit Mukherjee
    Anantha Simha
    Year: 2018
    Distributed Optimization Framework for Industry 4.0 Automated Warehouses
    DOI: 10.4108/eai.27-6-2018.155237
Ajay Kattepur1,*, Hemant Kumar Rath1, Arijit Mukherjee1, Anantha Simha1
  • 1: Embedded Systems & Robotics, TCS Research & Innovation, India
*Contact email:


Robotic automation is being increasingly proselytized in the industrial and manufacturing sectors to increase production efficiency. Typically, complex industrial tasks cannot be satisfied by individual robots, rather coordination and information sharing is required. Centralized robotic control and coordination is ill-advised in such settings, due to high failure probabilities, inefficient overheads and lack of scalability. In this paper, we model the interactions among robotic units using intelligent agent based interactions. As such agents behave autonomously, coordinating task/resource allocation is performed via distributed algorithms. We use the motivating example of warehouse inventory automation to optimally allocate and distribute delivery tasks among multiple robotic agents. The optimization is decomposed using primal and dual decomposition techniques to operate in minimal latency, minimal battery usage or maximal utilization scenarios.