Human motion provides rich priors for training general-purpose humanoid control policies, but raw demonstrations are often incompatible with a robot’s kinematics and dynamics, …
Recent work in reinforcement learning has shown that incorporating structural priors for articulated robots, such as link connectivity, into policy networks improves learning …
We present a novel and minimalistic design of an aerial-terrestrial robot DASH: Ducted Aerial Spring Hopper. The goal is to enable both aerial and ground locomotion capabilities on …
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