In the ambitious Treaty of Aachen, Germany and France are uniting their strengths in the field of artificial intelligence (AI) in order to reinforce economic sovereignty and make the economy more resilient. The Franco German collaboration will support the development of the shared ecosystem for AI research and innovation.

The global health and economic crises caused by the pandemic presents new challenges and possibilities for AI solutions. AI solutions have the potential to accelerate the development of new products and services.

Our consortium strategy is to develop AI solutions that achieve these goals while also adding significant value to the industry.


Fraunhofer Institute for Machine Tools and Forming Technology IWU

Since its foundation 1991, the IWU has been working in the field of automation and in particular process and quality monitoring and micro manufacturing technology as an absolutely essential field of research in order to be able to operate successfully in the international research landscape in the fields of machine construction, production technology and factory automation. The realization of processing, analysis and modelling of machine and factory data are just as much an elementary competence of the Fraunhofer IWU, as it is the detection of correlations, trends and anomalies in data using visual analysis methods and tools for statistical evaluations. Software modules are developed specifically for the respective applications that allow automatic analyses and forecasts. As a framework for software developments and applications is the tool Xeidana, developed at the Fraunhofer IWU. Xeidana is an extensible development environment for data analysis tasks in the industrial sector. The know-how available at the Fraunhofer IWU in the field of AI and Machine Learning is made available in numerous projects and publications both to the scientific community and, above all, to SME.

Website Fraunhofer IWU

Role in the Project

  • Object detection and tracking, as well as path planning, on the industrial use case “car underbody check”.
  • Monitoring the process.
  • Inline quality control.

Hochschule München University of Applied Sciences

The Munich University of Applied Sciences (HM) was founded in 1971 and is one of the largest universities for applied sciences in Germany. Hochschule München is technically oriented; the university’s comprehensive range of disciplines allows a holistic and interdisciplinary approach to topics in education and research. The university offers a practice-oriented academic education to its students in the areas of technology. The foundation of the institute for machine learning and intelligent system applications 2020 enlarges the base for research activities. The robotic laboratory of the Department of Applied Sciences and Mechatronics provides a background of robotic applications based on force and image processing sensors for industrial applications as well as human-robot-collaboration. Driven on the equipment of cobots with force-torque sensors, the research of a combined intelligent sensor usage for safety and applications is focused in the lab.

Website Munich University of Allpied Sciences

Role in the Project

  • Development of a laboratory demonstrator focusing on force and torque sensor control and processing.
  • Development of a demonstrator for human robot collaboration with self-learning force pressure limitation.
  • Development of a synchronized application process existing of a shared workspace between two robots.


Founded in 2019, Inbolt strives to democratize industrial robotics’ computer vision. Their innovation, GuideNOW, a real-time 3D vision and AI-driven robot guidance system, makes it possible for robots to dynamically locate workpieces and adjust their path, eliminating fixtures, indexing, and integration expenses. Elevate your efficiency by automating pick, tighten, test and glue tasks rapidly and flexibly!

Website Inbolt

Role in the Project

  • Develop a new AI processor and circuit board (PCB) and ensure the best latency and the lowest energy consumption.
  • Integrate into a WP6 defined platform to ensure the communication between the processor and the robot.
  • To be the project backbone and connect the different consortium members’ technologies.

Ecole Nationale Supérieure d’Arts et Métiers

ENSAM is a leading science & technology Grande École in France with an international reputation in education and research, and is one of France’s oldest engineering schools pecializing in mechanical, industrial and energy engineering. ENSAM, founder member of the French Alliance for Industry of the Future, is a key player in accompanying French and European industry, through its high-level academic programs and its cutting-edge research activities in the major fields of Industry 4.0, mainly cobotics, advanced manufacturing systems, production systems, virtual & augmented reality. ENSAM, through the LISPEN Laboratory, specializes in industrial robotic applications. ENSAM investigates robotic cell design and advanced control algorithms for increasing the technological maturity of innovative robotic solutions in the fields of machining, assembly and human-robot interaction. Current research focuses on AI-based robotics include online trajectory generation (fast and deterministic reaction to unforeseen events), advanced and autonomous calibration of robotic cells, robust visual servoing, and self-learning of grasping/assembly process.

Website Arts et Métiers

Role in the Project

  • Development of a collaborative robotic demonstrator combining fast and robust object position recognition and grasp angle detection, with time and energy reduction of the overall process.
  • Development of a dedicated demonstrator for AI-based visual servoing with optimization of actuation and perception pipeline for efficiency and robustness regarding the heterogeneity of parts and lighting conditions.

Subcontracted Partners

Associated Partners