We introduce judo, a software package designed to help develop shared tools for prototyping, benchmarking, and deploying sampling-based controllers.
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Robotic Dexterous Manipulation via Anisotropic Friction Modulation using Passive Rollers
We present the design and analysis of a robotic fingertip equipped with passive rollers that can be selectively braked or pivoted to modulate contact friction...
NovaFlow: Zero-Shot Manipulation viaActionable Flow from Generated Videos
We present NovaFlow, an autonomous manipulation framework that converts a task description into an actionable plan for a target robot without any demonstrations.
The RAI Institute Robot Lab: Studying Human Attitudes Towards Robots Through Experience
How a hands-on “Drive-a-Spot” experience significantly increased participants’ comfort with and perceived suitability for robots.
Pop-Up Encounters with Spot: Shaping Public Perceptions of Robots Through Hands-On Experience
In this study, we investigate how interacting with Boston Dynamics’ Spot, an agile, state-of-the-art quadruped robot, in a public pop-up booth affects perceptions of comfort...
Meet “Roadrunner”: a bipedal, wheeled robot for multi-modal locomotion
Roadrunner can stand up from the ground, drive with its wheels side-by-side, or shift them in-line.
Flip Stunts on Bicycle Robots using Iterative Motion Imitation
This work demonstrates a front-flip on bicycle robots via reinforcement learning, particularly by imitating reference motions that are infeasible and imperfect. To address this, we...
Lazy Anytime Planning for the Dubins Moving Target Traveling Salesman Problem with Obstacles
The Dubins Moving Target Traveling Salesman Problem with Obstacles (Dubins MT-TSP-O) seeks an obstacle-free trajectory for an agent with a fixed speed and minimum turning...
From Reflection to Repair: A Scoping Review of Dataset Documentation Tools
We examine the motivations behind building documentation tools, how authors conceptualize documentation practices, and how these tools connect to existing systems, regulations, and cultural norms.
Dull, Dirty, Dangerous: Understanding the Past, Present, and Future of a Key Motivation for Robotics
In robotics, the concept of “dull, dirty, and dangerous” (DDD) work has been used to motivate where robots might be useful. In this paper, we...
RAI Institute 2025: A Year of Innovation for Robotics and AI
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...
Dexterous Contact-Rich Manipulation via the Contact Trust Region
We present the Contact Trust Region (CTR), which captures the unilateral nature of contact while remaining efficient for computation.