Colloquia

Samenvatting

Since the introduction of the steam engine, the need for manual labor has been reducing. Robotics and AI are currently at the frontier of this development. Agriculture is no exception in this regard. GPS-guided tractors, camera hoeing machines, and GPS data-guided spraying machines are examples of current innovations. Furthermore, the agricultural machine market is seeing the emergence of the first (autonomous) robotic systems.

Where conventional farmers rely on spray applications, the ecological farmer combines several methods for different weed types. Most of the weeds In ecological farming can be removed using cost-effective mechanical means, yet the weeds the closest to the crop cannot be removed this way. These are currently removed by teams of (seasonal) laborers who remove the weeds by hand. Such a team removes the weeds on roughly one hectare per day at high seasonal costs.

The high cost and low speed of this manual labor make this an interesting market for robotic systems. Several companies are aiming to develop such systems. This thesis explores the possibilities for improving one such system with a German company. This is done through qualitative research with Dutch and German farmers, aiming to identify and explore different factors in the design of ecological weeding robots.