South Korean Humanoid Robot Startup Robros Announces World Action Model, Targets 2027 Open-Source Release
At NVIDIA AI Day Seoul, South Korean startup Robros unveiled its 'Real-to-Sim-to-Real' training pipeline and proprietary World Action Model (WAM), aiming to open-source the model in 2027.
South Korean humanoid robot startup Robros announced its latest technology roadmap on November 10 during the 'NVIDIA Physical AI Startup Connect' session at NVIDIA AI Day Seoul 2026. The presentation was led by Im Dae-gyu (임대규), the company's Chief AI Officer (CAIO). Key announcements included a 'Real-to-Sim-to-Real' training methodology and a proprietary 'World Action Model' (WAM).
According to the launch details, the 'Real-to-Sim-to-Real' approach involves creating a digital twin of actual work environments within a virtual space. Robots are trained in this simulation using NVIDIA's Isaac Sim, Isaac Lab, and Omniverse platforms, before the learned actions are transferred to physical robots for validation. This method aims to reduce the time and cost associated with repeated trial-and-error in the real world and mitigate dangerous operations. Robros has already reconstructed its laboratory environment using this method and validated box and manufacturing part handling tasks on its proprietary humanoid robot, IGRIS-C.
Additionally, Robros revealed plans to develop the WAM, an AI model designed to understand surrounding environments and generate corresponding robot actions. Currently, the model is undergoing pre-training using simulation data, videos of human operations, and data collected from actual robot deployments. The company explicitly stated that it targets releasing the WAM as an open-source project in 2027. If realized, this would provide global robot developers with a foundational action-generation model based on a simulation-first strategy.
Robros indicated that it will expand proof-of-concept (PoC) initiatives in manufacturing and logistics while simultaneously advancing its own AI model development and field data accumulation. Im emphasized that deploying humanoid robots in industrial settings requires data reflecting diverse working environments and validation technologies, stating that the company will enhance robot operational capabilities through its proprietary platform and simulation-based training.