By Topic:
By Type:
Presented at RSS 2026, Q2RL (Q-Estimation and Q-Gating from Behavior Cloning for Reinforcement Learning) is a method that avoids catastrophic forgetting when transitioning from offline...
Automatically converting demos into labeled datasets to enable the rapid training of task-specific object detectors that outperform existing state-of-the-art VLMs.
We’ll be presenting robotic research that includes contact-rich bimanual manipulation and policy learning, an open source package for sample-based Model Predictive Control (MPC), how to...
How AnyTask and ExpertGen Bridge the Sim-to-Real Gap
Redesigning how we collect bespoke data for manipulation tasks.
We propose a framework to help the robotics community explore how automation impacts jobs that are considered dull, dirty, dangerous (DDD).
AthenaZero is a robotic manipulator built to tackle dynamic tasks like a human arm. This fast, precise robot can switch in an instant from a...
How a hands-on “Drive-a-Spot” experience significantly increased participants’ comfort with and perceived suitability for robots.
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...
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
Unlocking physical capabilities with artificial intelligence to build the next generation of machines.
