Autonomous mobile robot travel under deadlock and collision prevention algorithms by agent-based modelling in warehouses

Date

2022-10-31

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor and Francis

Department

Type

Article

ISSN

1367-5567

Format

Free to read from

Citation

Eroglu Turhanlar E, Ekren BY, Lerher T. (2022) Autonomous mobile robot travel under deadlock and collision prevention algorithms by agent-based modelling in warehouses. International Journal of Logistics Research and Applications, Available online 31 October 2022

Abstract

Recent dramatic increase in e-commerce has also increased the adoption of automation technologies in warehouses. Autonomous mobile robots (AMRs) are from those technologies widely utilized in warehouse operations. It is important to design the operation of those robotic systems in such a way that, they meet the current and future system requirements correctly. In this paper, we study flexible travel of AMRs in warehouses by developing smart deadlock and collision prevention algorithms on agent-based modelling. By that, AMR agents can interact with each other and environment, so that they can make smart decisions maximizing their goals. We compare the performance of the developed flexible travel system with non-flexible designs where there is a single AMR dedicated to a specific zone so that no deadlock or collision possibility takes place. The results show that AMRs may provide up to 39% improvement in the flexible system compared to its non-flexible design.

Description

Software Description

Software Language

Github

Keywords

Agent-based simulation, deadlock prevention, autonomous vehicle, autonomous mobile robots, deadlock and collision

DOI

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

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Relationships

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