4 citations · 16 across the 29 of their papers we have counts for
30 papers
Do My Samples Help? Compute Budget Allocation for Real-World Sampling-Based MPC in Contact-Rich Manipulation
Magnus Dierking, João Carvalho, Vince Kurtz +3
Sampling-based model predictive control (SMPC) is increasingly practical for contact-rich manipulation because GPU-based physics simulators enable real-time evaluation of large num…
Shooting for Contact: Contact-Implicit Multiple Shooting for Dynamic Motion Retargeting
Sergio A. Esteban, Jason H. K. Siu, Derrick Mach +4
Motion retargeting approaches often prioritize kinematic similarity over whole-body dynamics, contact consistency, and actuation limits, yielding references that are difficult for…
Constrained Flow Matching via Lagrangian Dual Flows
Vince Kurtz, Alexander Davydov
Flow matching is a powerful tool for generative modeling, but emerging applications in robotics, planning, and control require inference-time constraints on generated outputs. Such…
On Surprising Effects of Risk-Aware Domain Randomization for Contact-Rich Sampling-based Predictive Control
Sergio A. Esteban, Junheng Li, Vince Kurtz +1
Domain randomization (DR) is widely used in policy learning to improve robustness to modeling error, but remains underexplored in contact-rich sampling-based predictive control (SP…
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…
Equality Constrained Diffusion for Direct Trajectory Optimization
Vince Kurtz, Joel W. Burdick
The recent success of diffusion-based generative models in image and natural language processing has ignited interest in diffusion-based trajectory optimization for nonlinear contr…
Supervised Learning for Stochastic Optimal Control
Vince Kurtz, Joel W. Burdick
Supervised machine learning is powerful. In recent years, it has enabled massive breakthroughs in computer vision and natural language processing. But leveraging these advances for…
DROP: Dexterous Reorientation via Online Planning
Albert H. Li, Preston Culbertson, Vince Kurtz +1
Achieving human-like dexterity is a longstanding challenge in robotics, in part due to the complexity of planning and control for contact-rich systems. In reinforcement learning (R…
Inverse Dynamics Trajectory Optimization for Contact-Implicit Model Predictive Control
Vince Kurtz, Alejandro Castro, Aykut Özgün Önol +1
Robots must make and break contact with the environment to perform useful tasks, but planning and control through contact remains a formidable challenge. In this work, we achieve r…
Temporal Logic Motion Planning with Convex Optimization via Graphs of Convex Sets
Vince Kurtz, Hai Lin
Temporal logic is a concise way of specifying complex tasks. But motion planning to achieve temporal logic specifications is difficult, and existing methods struggle to scale to co…
Mixed-Integer Programming for Signal Temporal Logic with Fewer Binary Variables
Vince Kurtz, Hai Lin
Signal Temporal Logic (STL) provides a convenient way of encoding complex control objectives for robotic and cyber-physical systems. The state-of-the-art in trajectory synthesis fo…
Robust Approximate Simulation for Hierarchical Control of Piecewise Affine Systems under Bounded Disturbances
Zihao Song, Vince Kurtz, Shirantha Welikala +2
Piecewise affine (PWA) systems are widely applied in many practical cases such as the control of nonlinear systems and hybrid dynamics. However, most of the existing PWA control me…
Contact-Implicit Trajectory Optimization with Hydroelastic Contact and iLQR
Vince Kurtz, Hai Lin
Contact-implicit trajectory optimization offers an appealing method of automatically generating complex and contact-rich behaviors for robot manipulation and locomotion. The scalab…
A More Scalable Mixed-Integer Encoding for Metric Temporal Logic
Vince Kurtz, Hai Lin
The state-of-the-art in optimal control from timed temporal logic specifications, including Metric Temporal Logic (MTL) and Signal Temporal Logic (STL), is based on Mixed-Integer C…
Active Perception and Control from PrSTL Specifications
Rafael Rodrigues da Silva, Vince Kurtz, Hai Lin
Next-generation intelligent systems must plan and execute complex tasks with imperfect information about their environment. As a result, plans must also include actions to learn ab…
Control Barrier Functions for Singularity Avoidance in Passivity-Based Manipulator Control
Vince Kurtz, Patrick M. Wensing, Hai Lin
Task-space Passivity-Based Control (PBC) for manipulation has numerous appealing properties, including robustness to modeling error and safety for human-robot interaction. Existing…
Mini Cheetah, the Falling Cat: A Case Study in Machine Learning and Trajectory Optimization for Robot Acrobatics
Vince Kurtz, He Li, Patrick M. Wensing +1
Seemingly in defiance of basic physics, cats consistently land on their feet after falling. In this paper, we design a controller that lands the Mini Cheetah quadruped robot on its…
Trajectory Optimization for High-Dimensional Nonlinear Systems under STL Specifications
Vince Kurtz, Hai Lin
Signal Temporal Logic (STL) has gained popularity in recent years as a specification language for cyber-physical systems, especially in robotics. Beyond being expressive and easy t…
Automatic Trajectory Synthesis for Real-Time Temporal Logic
Rafael Rodrigues da Silva, Vince Kurtz, Hai Lin
Many safety-critical systems must achieve high-level task specifications with guaranteed safety and correctness. Much recent progress towards this goal has been made through contro…
A Smooth Robustness Measure of Signal Temporal Logic for Symbolic Control
Yann Gilpin, Vince Kurtz, Hai Lin
Recent years have seen an increasing use of Signal Temporal Logic (STL) as a formal specification language for symbolic control, due to its expressiveness and closeness to natural…
Approximate Simulation for Template-Based Whole-Body Control
Vince Kurtz, Patrick M. Wensing, Hai Lin
Reduced-order template models are widely used to control high degree-of-freedom legged robots, but existing methods for template-based whole-body control rely heavily on heuristics…