4 citations · 16 across the 29 of their papers we have counts for
4 papers · 1 filter
CENIC: Convex Error-controlled Numerical Integration for Contact
Vince Kurtz, Alejandro Castro
State-of-the-art robotics simulators operate in discrete time. This requires users to choose a time step, which is both critical and challenging: large steps can produce non-physic…
Risk-Guided Diffusion: Toward Deploying Robot Foundation Models in Space, Where Failure Is Not An Option
Rohan Thakker, Adarsh Patnaik, Vince Kurtz +10
Safe, reliable navigation in extreme, unfamiliar terrain is required for future robotic space exploration missions. Recent generative-AI methods learn semantically aware navigation…
Reduced-Order Model Guided Contact-Implicit Model Predictive Control for Humanoid Locomotion
Sergio A. Esteban, Vince Kurtz, Adrian B. Ghansah +1
Humanoid robots have great potential for real-world applications due to their ability to operate in environments built for humans, but their deployment is hindered by the challenge…
Generative Predictive Control: Flow Matching Policies for Dynamic and Difficult-to-Demonstrate Tasks
Vince Kurtz, Joel W. Burdick
Generative control policies have recently unlocked major progress in robotics. These methods produce action sequences via diffusion or flow matching, with training data provided by…