Distributed Optimization Framework for Industry 4.0 Automated Warehouses

Abstract

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.

Authors and Affiliations

Ajay Kattepur, Hemant Kumar Rath, Arijit Mukherjee, Anantha Simha

Keywords

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Distributed Optimization Framework for Industry 4.0 Automated Warehouses

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 co...

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  • EP ID EP46083
  • DOI http://dx.doi.org/10.4108/eai.27-6-2018.155237
  • Views 286
  • Downloads 0

How To Cite

Ajay Kattepur, Hemant Kumar Rath, Arijit Mukherjee, Anantha Simha (2018). Distributed Optimization Framework for Industry 4.0 Automated Warehouses. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 5(15), -. https://europub.co.uk/articles/-A-46083