In essence, it is about combining two platform worlds: the virtual twin technologies of the French software company Dassault Systèmes and the cognitive robotics of the German company Neura Robotics. Specifically, Neuraverse, a learning platform that networks robots, people and data, is to be merged with the '3DEXPERIENCE' platform from Dassault Systèmes. Virtual images of products, processes and entire industrial plants are created there.

The idea behind this is that planning, simulation, AI training and the use of real robots can no longer be seen as separate steps, but as a continuous process. For example, the humanoid robot '4NE1' from Neura Robotics is to be integrated directly into the virtual development environment. Other robot types are to follow.

In contrast to previous approaches, which limit virtual twins to the simulation of individual components or processes, this is the first time that a continuous end-to-end pipeline has been realized - from the virtual model to the operational use of the robot, according to the company. This should enable companies to plan products, processes and environments directly on the platform and use Neura robots as a native, ready-to-use and fully integrated system from day one.

The companies speak of a closed loop: Digital models form the basis of real applications, while the robots used collect data during operation and learn from it. The performance of the systems should improve with each use. The project is embedded in Dassault Systèmes' 3D UNIV+RSES approach, which aims to bring together virtual twins, robotics and AI in a shared development environment.

The partners see further fields of application beyond industry. The 'HomeByMe' platform, for example, combines virtual living environments with robotics and uses them as a training environment for AI systems. This could lead to applications in the areas of assistance, service and everyday automation.

According to the companies, the cooperation covers the entire life cycle of robotic systems: from planning and simulation to deployment. The aim is to accelerate development and scaling and to create an ecosystem in which applications and AI models are jointly created and further developed.