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There’s a world where robots integrate seamlessly into our daily work, and eventually our cities and home lives. When the RAI Institute was founded in...
Researchers at the RAI Institute have built a low-impedance platform to study dynamic robot manipulation. In this demo, robots play a game of catch and...
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...
Spot uses dynamic whole-body manipulation to autonomously upright, roll, drag, and stack 15kg car tires using an approach that combines reinforcement learning and sampling-based optimization
Abstract: The ability to flexibly leverage limbs for loco-manipulation is essential for enabling autonomous robots to operate in unstructured environments. Yet, prior work on loco-manipulation...
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,...
While AI has mastered language, getting robots to move swiftly and effortlessly through the unstructured world has not been solved. RAI Institute is building robots...
Unlocking physical capabilities with artificial intelligence to build the next generation of machines.
Researchers at the RAI Institute have bridged the gap between kinematic motion diffusion models and physics-based control policies with a new guided diffusion framework called...
This workshop aims to gather experts in 3D human/animal modeling, motion generation algorithms, and robotics to review recent progress and chart the next steps for...
Researchers present Diffuse-CLoC, a guided diffusion framework for physics-based look-ahead control that enables intuitive, steerable, and physically realistic motion generation.
