Introducing the Robotics and AI Institute, formerly known as The AI Institute.
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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.
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...
Introducing Theia, a vision foundation model for robotics developed by researchers at the Institute.
The annual Conference on Robot Learning (CoRL) takes place this week, November 6-9 in Munich, Germany. Read on to learn more about our accepted publications.
We present a fully autonomous real-world RL framework for mobile manipulation that can learn policies without extensive instrumentation or human supervision.
Robotic manipulation is challenging and data-driven approaches typically require large amounts of data or expert demonstrations. Therefore, we introduce a motion planner for dexterous and...
Researchers at the RAI Institute propose GCR (Goal-Contrastive Rewards), a dense reward function learning method that can be trained on passive video demonstrations.
