humanoids gain human-like agility with ASAP framework
Researchers just introduced ASAP, a two-stage framework that bridges the sim-to-real physics gap for humanoid robots. By pairing simulated pre-training with a real-world residual action model, the team demonstrated agile whole-body skills on a Unitree G1 robot with significantly reduced tracking errors. Why it matters: It offers a practical path to dynamic robot agility without manual parameter tuning.