We’ve opened a free, hands-on robot lab for the summer! Plan your visit.
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This workshop on August 11 aims to gather experts in 3D human/animal modeling, motion generation algorithms, and robotics to review recent progress and chart the...
Researchers present Diffuse-CLoC, a guided diffusion framework for physics-based look-ahead control that enables intuitive, steerable, and physically realistic motion generation.
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...
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...
Researchers at the Institute examine the effectiveness of linear feedback controllers for contact-rich robotic manipulation, with differentiable simulations that use contact smoothing.
Researchers present a low-cost data generation pipeline that integrates physics-based simulation, human demonstrations, and model-based planning to efficiently generate large-scale, high-quality datasets for contact-rich robotic...
Cross-embodiment imitation learning enables policies trained on specific embodiments to transfer across different robots, unlocking the potential for large-scale imitation learning that is both cost-effective...
The Robotics and AI Institute aims to accelerate robotics and artificial intelligence research by bringing together top talent and the best elements of industry and...
