Economic relevance of autonomous field robots in maize production

The economic relevance of autonomous field robots in real-world farming systems has not yet been sufficiently quantified. This study analyses the application of the AgBot 2.055W4 in maize production and related logistical processes on two farms in northwestern Germany. The economic assessment is based on a scenario-based simulation of robotic field operations under different supervision levels (SL), complemented by work-time data on logistical processes. The farms are modelled within a hypothetical machinery cooperation to ensure a consistent representation of resource allocation. A cost–benefit modelling framework is applied, focusing on the relative cost burden of robot use and the contribution of automation benefits to maize production revenues. Across the analysed supervision scenarios, net costs correspond to 28–45 % of output excluding direct and work execution costs, indicating that robot-related costs represent a substantial share of the economic margin available from maize production. Automation benefits contribute at most about 3 % to total production revenues. Although the SL = 0 scenario yields the lowest net costs, a low supervision range (SL = 0.10–0.25) is identified as the most economically plausible option under realistic conditions. Overall, this indicates a comparatively high cost burden alongside a limited economic contribution of automation benefits. While the cost–performance analysis provides important insights, it captures only part of the factors shaping adoption decisions. In practice, adoption may also be driven by labour availability and broader organisational conditions that are not fully reflected by cost-based indicators.