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Mar 19, 2025

Video

Athletic Intelligence

Reinforcement Learning Accelerates Humanoid Behavior Production

Reinforcement learning is used to speed the production of behavior for the Atlas humanoid robot. At the heart of the learning process is a physics-based simulator that generates training data for a variety of maneuvers. The control policy tracks and controls retargeted human motion data. Each maneuver is created with data from about 150 million runs of the simulator and transferred zero-shot to the hardware. This work is part of a collaboration between the RAI Institute and Boston Dynamics.

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Feb 27, 2025

Stunting with Reinforcement Learning

In this demo, Ultra Mobile Vehicle (UMV) drives, turns, jumps, tricks, and comes to a sudden stop called a track-stand. All of the driving, landings, balance, and track-stands are done using reinforcement learning.
Video
Athletic Intelligence
Feb 27, 2025

Spot Speeds Up

Using reinforcement learning, we trained policies for Spot that allow the robot to achieve record running speeds of 11.5 mph (5.2 m/s) — over three times faster than Spot's default max speed.
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Athletic Intelligence

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