A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems

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Abstract

Real-time path planning for large, dense grid-based automated guided vehicle (AGV) systems, used for example to sort parcels, is challenging. Most approaches described in the literature are not fast enough for real-time control or are not able to avoid congestion. This paper presents a dynamic approach using a graph-representation of the grid system layout with vertex weights that are updated over time. By means of an extensive discrete-event simulation, we show that the proposed path planning approach significantly increases the throughput compared to existing approaches. Furthermore, it enables the recovery from deadlock situations.

Original languageEnglish
Article number105046
Number of pages10
JournalComputers and Operations Research
Volume123
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Automated guided vehicle
  • Centralized control
  • Deadlock recovery
  • Discrete event simulation
  • Dynamic path planning
  • Real-time control

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