Discrete Event Simulations for Scalability Analysis of Robotic In-Field Logistics in Agriculture – A Case Study

Das, Gautham, Cielniak, Grzegorz, From, Pal and Hanheide, Marc (2018) Discrete Event Simulations for Scalability Analysis of Robotic In-Field Logistics in Agriculture – A Case Study. In: IEEE International Conference on Robotics and Automation, Workshop on Robotic Vision and Action in Agriculture, 21-25 May 2018, Brisbane.

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Discrete Event Simulations for Scalability Analysis of Robotic In-Field Logistics in Agriculture – A Case Study
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Item Type:Conference or Workshop contribution (Poster)
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Abstract

Agriculture lends itself to automation due to its labour-intensive processes and the strain posed on workers in the domain. This paper presents a discrete event simulation (DES) framework allowing to rapidly assess different processes and layouts for in-field logistics operations employing a fleet of autonomous transportation robots supporting soft-fruit pickers. The proposed framework can help to answer pressing questions regarding the economic viability and scalability of such fleet operations, which we illustrate and discuss in the context of a specific case study considering strawberry picking operations. In particular, this paper looks into the effect of a robotic fleet in scenarios with different transportation requirements, as well as on the effect of allocation algorithms, all without requiring resource demanding field trials. The presented framework demonstrates a great potential for future development and optimisation of the efficient robotic fleet operations in agriculture.

Keywords:Robotics, Discrete event simulation, Agriculture, Robotic fleet, In-field logistics
Subjects:H Engineering > H671 Robotics
D Veterinary Sciences, Agriculture and related subjects > D400 Agriculture
J Technologies > J960 Transport Logistics
D Veterinary Sciences, Agriculture and related subjects > D471 Agricultural Machinery
Divisions:College of Science > School of Computer Science
ID Code:32170
Deposited On:11 Jul 2018 15:55

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