5 papers · 1 filter
CrossSafe: Towards Cross-Embodiment Latent Safety Filters
Ihab Tabbara, Yuxuan Yang, Hussein Sibai
Cross-embodiment learning has shown that a single model, such as a vision-language-action (VLA) model, can learn state representations and manipulation skills that can be applied a…
Towards General Language-Conditioned Latent Safety Filters
Ihab Tabbara, Yuxuan Yang, Hussein Sibai
Robot policies are becoming increasingly general, with vision-language-action (VLA) models enabling a single policy to execute diverse tasks specified in natural language. Safe dep…
On the Limits of Sampling-Based Reachability: Geometry, Dynamics, and Sample Complexity
Jixian Liu, Ihab Tabbara, Hussein Sibai +1
Reachability analysis is central to safety-critical control, robotics, and neural network verification, but classical computational methods, such as Hamilton--Jacobi reachability a…
Designing Latent Safety Filters using Pre-Trained Vision Models
Ihab Tabbara, Yuxuan Yang, Ahmad Hamzeh +2
Ensuring safety of vision-based control systems remains a major challenge hindering their deployment in critical settings. Safety filters have gained increased interest as effectiv…
Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees
Xinhang Ma, Junlin Wu, Hussein Sibai +2
Ensuring safety in autonomous systems with vision-based control remains a critical challenge due to the high dimensionality of image inputs and the fact that the relationship betwe…