Data factories, motion-capture labs and world models now compete to teach humanoids new skills. Follow how robots and the people beside them are trained, with The Humanoid Group.
What moved in robot training this year.
270,000 hours of real-world manipulation data behind Generalist's GEN-0 model (Generalist AI, 2025)
$100M+ a year that robotics companies spend on real-world movement data (PYMNTS, 2026)
<200 examples to adapt Gemini Robotics On-Device 2 to a new two-arm robot (The Robot Report, 2026)
Runway unveils Praxis-1, a robot control model built on video pretraining
· Research
Video AI company Runway introduced Praxis-1, an open-weight world action model that turns large-scale video pretraining into robot control instead of relying mainly on scarce robot demonstrations. Runway says testing policies inside its world model predicted real-world results with 0.95 correlation. Early partners are testing it, and a public release is planned.
Why it matters: If simulated tests reliably predict real results, teams can screen new robot skills before spending time on hardware. Ask any vendor how its virtual evaluations compare with measured results on site.
Innodata opens a motion-capture lab to supply and verify humanoid training data
· Launch
Data company Innodata opened a motion-capture lab in Ridgefield Park, New Jersey, using Vicon infrared cameras that track movement with sub-millimeter accuracy. It sells ready-made and custom motion datasets for humanoids and other robots, retargets data across platforms, and offers independent performance evaluation and safety benchmarking.
Why it matters: Third-party testing gives buyers a check on maker claims. Before a pilot, ask whether a robot's skills were measured independently and whether you can rerun the same tests at your site.
Japanese consortium opens a school where VR operators teach humanoids factory work
· Deployment
J-HRTI, a consortium of five companies including Tsumura and Yamazen, opened a facility in Narashino, Chiba Prefecture, that can hold up to 40 Chinese-made humanoids. Operators wearing VR headsets control the robots in mock work areas to collect training data, aiming to deploy them on simple tasks such as moving materials by March 2027.
Why it matters: Pooling teleoperation data spreads the cost of teaching robots across several firms. If you join or buy into such a program, agree who owns the recorded data and the skills trained on it.
Robotics in the Workplace: An Overview— NIOSH, US Centers for Disease Control and Prevention. How industrial, service and collaborative robots change workplace hazards, and what NIOSH studies about working beside them.
Recent Advances in Robot Learning from Demonstration— Annual Review of Control, Robotics, and Autonomous Systems. Peer-reviewed survey of imitation learning methods, when demonstrating beats scripting, and the problems still open.
Robot Learning From Randomized Simulations: A Review— Frontiers in Robotics and AI. Peer-reviewed review of sim-to-real work: why the reality gap appears and how randomising the simulator helps policies transfer.
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