# Figure AI uses reinforcement learning to give Figure 02 humanoid robot a natural, human-like walk

- Source: Figure AI
- Published: 2025-03-25T00:00:00.000Z
- RoboHot: https://robohot.news/en/items/bl4urmn1vc3gbhm7spibhug7m
- Original: https://www.figure.ai/news/reinforcement-learning-walking

## Summary

Figure AI released an end-to-end reinforcement learning walking controller that lets the Figure 02 humanoid robot learn a human-like gait in simulation by imitating human reference trajectories through rewards, including heel strike, toe push-off, and arm swing. Training runs in parallel across thousands of robots in GPU-accelerated physics simulation, collecting years of simulated data in hours, and combines domain randomization with kHz-level torque feedback control to achieve zero-shot transfer to the real robot; 10 Figure 02 units run the same neural network without individual tuning.

## Why it matters

The original text provides details on the training method and sim-to-real transfer for Figure 02's reinforcement-learning-based human-like walking, offering insight into its technical approach.