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

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.