3 citations · 4 across the 13 of their papers we have counts for
6 papers · 1 filter
ResSafe: Learning Safety Filtering with Residual Reinforcement Learning for Humanoids
Gechen Qu, Tong Zhang, Bike Zhang +4
Safe control of humanoid robots remains challenging due to their high-dimensional dynamics, contact-rich interactions, and sensitivity to disturbances. Although reinforcement learn…
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…
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…
Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walker
Xingpeng Xia, Jason J. Choi, Ayush Agrawal +3
Learning-based approaches have recently shown notable success in legged locomotion. However, these approaches often lack accountability, necessitating empirical tests to determine…
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems
Jason J. Choi, Fernando Castañeda, Wonsuhk Jung +3
As the use of autonomous robots expands in tasks that are complex and challenging to model, the demand for robust data-driven control methods that can certify safety and stability…