Neura Robotics opens Physical AI training centre in Germany by end of 2026

Neura Robotics announced a partnership with RWTH Aachen University to establish a new Physical AI training facility called Neura Gym RWTH Aachen, scheduled to open by the end of 2026 at the university's Hightech Campus Melaten in Germany. This facility forms part of a global expansion of Neura Gyms — purpose-built centres where robots train using real-world environments alongside simulation to generate data for AI development.

The company is currently developing ten Neura Gyms worldwide, with five expected to be operational across Europe, the United States and China by the end of 2026. According to Neura, these facilities are designed to address one of the biggest challenges in Physical AI: the shortage of real-world training data. The data collected will feed into the company's cloud-based Neuraverse platform, enabling robots to learn new skills and allowing industrial partners to validate applications before full-scale deployment.

David Reger, founder and CEO of Neura Robotics, explained the core problem: "The biggest bottleneck in physical AI is no longer intelligence, it's experience." He emphasized that robots learn by interacting with the real world and that every company possesses expertise no AI model currently has. "Our Gyms transform this knowledge into deployable robot skills while every partner remains fully in control of its own data," Reger said.

The Aachen facility will cover approximately 3,000 square metres and will support research, AI training and industrial validation of intelligent and humanoid robots. Around 20 university institutes will participate, with applications focusing on manufacturing, automotive, the circular economy and medical technology. Professor Dr Ulrich Rüdiger, rector of RWTH Aachen University, highlighted the collaboration as advancing the university's transfer strategy: "By combining this scientific leadership with a leading high-tech pioneer, we are creating a unique infrastructure for the skilled professionals of tomorrow and securing Germany's leading position in the global AI competition."

The Aachen centre joins a second major facility, TUM RoboGym at Munich Airport, being developed with the Technical University of Munich and also expected to open in the fourth quarter of 2026. Neura stated that the expanding Gym network is intended to provide companies with open infrastructure for developing, testing and deploying Physical AI systems while accelerating the adoption of cognitive robotics worldwide.

Neura Robotics has identified a fundamental constraint in Physical AI development: the shortage of real-world training data. Unlike large language models trained on vast text corpora, robots require hands-on interaction with physical environments to learn generalizable skills. The company's response is to establish purpose-built training centres — Neura Gyms — where robots can operate in realistic settings while generating data fed into a shared cloud platform.

The partnership with RWTH Aachen University is strategically anchored in the institution's decades of strength in mechanical engineering, electrical engineering and computer science. By co-locating a Neura Gym with academic expertise across 20 institutes, the facility becomes both a research hub and an industrial validation ground. The focus areas — manufacturing, automotive, circular economy and medical technology — represent sectors where robotic automation is economically significant but currently constrained by the difficulty of training systems for real-world deployment.

Neura's broader network strategy, with five facilities across three continents and a second major site at Munich Airport (opening in the fourth quarter of 2026), suggests the company views distributed, standardized training infrastructure as essential to scaling cognitive robotics adoption. Each partner retains control of its own data while contributing to a shared knowledge base accessible via the Neuraverse platform, creating an open-infrastructure model that aims to accelerate deployment cycles for industrial users.

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