Advanced Navigation and Artificial Intelligence Techniques: Team Carbonite's Winning Strategies at the Field Robot Event 2023 - Mannchen, Samuel; Mayer, Jonas; Schőnegg, Janis Lion; Fauser, Klara (Agricultura Scientia, 2025)
An approach to address current challenges in agriculture caused by climate change, the increasing global population and the loss of biodiversity is precision farming, for which agricultural robotics is a key enabler. The Field Robot Event (FRE) 2023 has challenged student teams to develop and improve autonomous agricultural robots. This paper presents the improvements to our field robot “Carbonite,” which is developed at the Schülerforschungszentrum (SFZ) Südwürttemberg. Our lightweight and compact robot design, supported by our advanced and efficient navigation algorithm, enabled our robot to quickly move through fields. Additionally, we introduced our newly developed system for targeted and precise application of water, fertilizer and herbicides, based on an intelligent gap detection algorithm to avoid wasting resources. Also, we trained an object recognition AI model based on the You Only Look Once (YOLO) models, allowing the robot to appropriately respond based on the type of obstacle. Carbonite managed to secure the first place in both the navigation task and the plant treatment task, benefiting from the lightweight design and the resulting high robot driving speed, enabling us to win the overall FRE 2023 contest.
Keywords: agricultural robotics; precision agriculture; sustainability; artificial intelligence