Researchers at Carnegie Mellon University and NVIDIA have developed an AI framework called ASAP that enables humanoid robots to perform advanced athletic maneuvers with exceptional agility. The framework, which addresses the challenge of dynamics mismatch between simulation and the real world, allows robots to replicate iconic moves like Cristiano Ronaldo's mid-air spin and Kobe Bryant's fadeaway jump shot.
Researchers have developed an AI framework that allows humanoid robots to execute advanced athletic maneuvers with exceptional agility. Carnegie Mellon University and NVIDIA have partnered to create Aligning Simulation and Real Physics that allows humanoids to execute moves like Cristiano Ronaldo’s iconic mid-air spin and Kobe Bryant’s signature fadeaway jump shot.
These are retargeted to humanoid robots and trained with a motion-tracking policy. Since direct deployment leads to performance loss, a second stage collects real-world data to identify discrepancies. According to researchers, a delta action model is then trained to compensate for these differences. Finally, the policy is fine-tuned with the delta model, allowing humanoid robots to adapt effectively to real-world physics.
ROBOTICS AI ATHLETICS SIMULATION DYNAMICS
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