Training and testing of agriculture robots in simulation

Artificial Intelligence (AI) and robotics can help farmers to produce higher-quality food and have less impact on the environment. However, training and testing of agriculture robots is time consuming and expensive, because this usually happens in the physical environment and often involves the robot breaking down. In our project, we create a digital version of the robot that is tested and trained in a simulated environment. This way, training and testing of robots becomes faster and cheaper.

Team members Saber and colleagues, in collaboration with EAISI: Meander van de Weijst, Andrea Favia, Vincent Fokke
Department Student Team
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