3 citations · 4 across the 13 of their papers we have counts for
6 papers · 1 filter
A Hamilton-Jacobi Reachability Framework with Soft Constraints for Safety-Critical Systems
Chams Eddine Mballo, Donggun Lee, Claire J. Tomlin
Traditional reachability methods provide formal guarantees of safety under bounded disturbances. However, they strictly enforce state constraints as inviolable, which can result in…
EigenSafe: A Spectral Framework for Learning-Based Probabilistic Safety Assessment
Inkyu Jang, Jonghae Park, Sihyun Cho +3
We present EigenSafe, an operator-theoretic framework for safety assessment of learning-enabled stochastic systems. In many robotic applications, the dynamics are inherently stocha…
Mechanistic interpretability for steering vision-language-action models
Bear Häon, Kaylene Stocking, Ian Chuang +1
Vision-Language-Action (VLA) models are a promising path to realizing generalist embodied agents that can quickly adapt to new tasks, modalities, and environments. However, methods…
When are safety filters safe? On minimum phase conditions of control barrier functions
Jason J. Choi, Claire J. Tomlin, Shankar Sastry +1
In emerging control applications involving multiple and complex tasks, safety filters are gaining prominence as a modular approach to enforcing safety constraints. Among various me…
Resolving Conflicting Constraints in Multi-Agent Reinforcement Learning with Layered Safety
Jason J. Choi, Jasmine Jerry Aloor, Jingqi Li +3
Preventing collisions in multi-robot navigation is crucial for deployment. This requirement hinders the use of learning-based approaches, such as multi-agent reinforcement learning…
Data-Driven Hamiltonian for Direct Construction of Safe Set from Trajectory Data
Jason J. Choi, Christopher A. Strong, Koushil Sreenath +2
In continuous-time optimal control, evaluating the Hamiltonian requires solving a constrained optimization problem using the system's dynamics model. Hamilton-Jacobi reachability a…