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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.
We introduce Judo, a software package designed to address this need. To facilitate rapid prototyping and evaluation, Judo provides robust implementations of common sampling-based MPC...
The IEEE International Conference on Robotics and Automation (ICRA) will take place May 19 – 23, 2025 in Atlanta, Georgia. ICRA serves as the premier...
This work presents an overview of the technical details behind a high-performance reinforcement learning policy deployment with the Spot RL Researcher Development Kit for low-level...
To move closer to the goal of next-generation hardware design capable of more human-like manipulation, researchers at the Institute have developed a new type of...
Researchers investigate how to leverage model-based planning and optimization to generate training data for contact-rich dexterous manipulation tasks.
Ultra Mobile Vehicle (UMV) learns to flip.
