160 citations · 403 across the 56 of their papers we have counts for
12 papers · 1 filter
Back on Track: Deployment-time Policy Improvement via World Model Planning
Colton Crosby, Hao Wang, Mac Schwager +1
State-of-the-art visuomotor policies are increasingly capable of executing complex tasks, yet can fail during deployment in ways they cannot predict or recover from on their own. I…
Where Small Mistakes Matter: Quantifying State Criticality for Imitation Learning
Yusuf Umut Ciftci, Joonwon Kang, Ajay Suresha Sathya +1
Imitation learning typically treats every demonstration state as equally important, optimizing a behavior-cloning objective uniformly across the dataset. Yet not all states are cre…
Context-Conditioned Hamilton-Jacobi Reachability for Adaptive Safety Filtering
Ali Fuat Sahin, Yunus Yazoglu, John Talbot +3
Hamilton-Jacobi reachability constructs safety certificates for specified dynamics and safety constraints, tying each certificate to the deployment context for which it is synthesi…
When Reasoning Helps Action: Monitoring and Steering Chain-of-Thought in Vision-Language-Action Policies
Sathwik Karnik, Joseph JR. Lee, Aryaman Gupta +1
Reasoning-enabled VLA policies expose chain-of-thought (CoT) traces that appear to explain and guide their actions, creating a potential interface for runtime safety through reason…
When World Models Lie: Adaptive Safety Analysis Under Wrong Imaginations
John Cao, Somil Bansal
World models offer a powerful substrate for safety reasoning in high-dimensional robotic systems, but they are also fallible: their predictions can be biased, miscalibrated, or con…
Hamilton-Jacobi Reachability for Hybrid Systems: Unified Goal-Driven Control with Safety Guarantees
Javier Borquez, Shuang Peng, Somil Bansal
Hybrid dynamical systems provide a powerful modeling framework for robotic systems, particularly in contact-rich environments. However, ensuring safety and performance in such syst…
Gradient-Free Neural Hamilton-Jacobi Reachability for Scalable Safety-Critical Control
Zeyuan Feng, Ali Fuat Sahin, Santiago Thorup +1
Hamilton-Jacobi (HJ) reachability provides a principled framework for synthesizing safety certificates and robust controllers for safety-critical robotic systems. However, applying…
Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation
Hao Wang, Joshua Bowden, Colton Crosby +1
Policy evaluation is a fundamental component of the development and deployment pipeline for robotic policies. In modern manipulation systems, this problem is particularly challengi…
Neural Backward Reach-Avoid Tubes with MPC Supervision for High-Dimensional Systems: An Application to Safe Spacecraft Docking
Santiago Thorup, Luca Castelletto, Zeyuan Feng +1
Autonomous spacecraft docking requires control policies that simultaneously ensure collision avoidance and target reachability under coupled, high-dimensional translational-rotatio…
Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control
Hao Wang, Nam Nguyen, Armand Jordana +2
Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state and input constraints. Althou…
Boundary Sampling to Learn Predictive Safety Filters via Pontryagin's Maximum Principle
James Dallas, Thomas Lew, John Talbot +3
Safety filters provide a practical approach for enforcing safety constraints in autonomous systems. While learning-based tools scale to high-dimensional systems, their performance…
Steering Away from Memorization: Reachability-Constrained Reinforcement Learning for Text-to-Image Diffusion
Sathwik Karnik, Juyeop Kim, Sanmi Koyejo +2
Text-to-image diffusion models often memorize training data, revealing a fundamental failure to generalize beyond the training set. Current mitigation strategies typically sacrific…