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A New Benchmark in Robot Juggling

AthenaZero can juggle barehanded using onboard vision feedback. By using multi-fingered hands, it can transition seamlessly between a wide range of juggling patterns.

Getting a Grip on Robotic Data Collection

To make sure the data collected transfers to the robot, we’ve co-designed handheld and robot grippers: same linkage mechanisms, same degrees of freedom, same force...

From Walking to Working: Spot Stacks Tires

Spot robot performs dynamic whole-body manipulation using a combination of reinforcement learning and sampling-based control. Behavior shown in the video is fully autonomous, including the...

Ultra Mobile Vehicle Expands Mobility Repertoire

Using reinforcement learning we have expanded the range of techniques the Ultra Mobile Vehicle (UMV) uses to handle terrain and obstacles, including hops, out-of-plane balance,...

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.

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.