Trustworthy AI AI "Made in Europe" Reduces Energy Consumption in Robotics By 25 Percent

Source: Fraunhofer IWU | Translated by AI 1 min Reading Time

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The research project Greenbot AI significantly reduces the energy consumption of industrial robots, making automation simpler, greener, and more resilient.

Robotics can be this simple and efficient: Controlled by 2D images, the robot picks up a component and, guided by force-torque control and intelligent AI, fits it into a second gear.(Image: Fraunhofer IWU)
Robotics can be this simple and efficient: Controlled by 2D images, the robot picks up a component and, guided by force-torque control and intelligent AI, fits it into a second gear.
(Image: Fraunhofer IWU)

With the flagship project Greenbot AI, Germany and France have demonstrated how trustworthy artificial intelligence “made in Europe” can make industrial automation more efficient and sustainable. According to a statement from the Fraunhofer Institute for Machine Tools and Forming Technology IWU, the Munich University of Applied Sciences, Inbolt SAS, and the French engineering school ENSAM, the system reduces the energy consumption of robots by more than 25 percent without requiring any hardware replacement.

The project was supported as part of the German-French funding call Innovation Projects on Artificial Intelligence Technologies for Risk Prevention, Crisis Management and Resilience. The goal: to strengthen Europe’s resilience and competitiveness through AI. Greenbot AI focused on optimizing reaction times, path planning, and energy efficiency in robotics, according to the project partners.

Through modular machine learning models and a lightweight system architecture, Greenbot AI enables industrial applications such as bin-picking, assembly, or quality control without requiring deep robotics expertise. Communication via UDP allows real-time control across various robot systems. Technically, the project focused primarily on the reaction and latency times of industrial robots, optimized path planning, and the execution of specific tasks during robot movement, according to reports.

Fraunhofer IWU led the consortium, while Inbolt, as a deep-tech startup, contributed its expertise in 3D vision and AI-based robot guidance. Munich University of Applied Sciences and ENSAM ensured scientific depth and practical transfer.

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