9 papers
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…
Safe Control using Learned Safety Filters and Adaptive Conformal Inference
Sacha Huriot, Ihab Tabbara, Hussein Sibai
Safety filters have been shown to be effective tools to ensure the safety of control systems with unsafe nominal policies. To address scalability challenges in traditional synthesi…
Statistically Assuring Safety of Control Systems using Ensembles of Safety Filters and Conformal Prediction
Ihab Tabbara, Yuxuan Yang, Hussein Sibai
Safety assurance is a fundamental requirement for deploying learning-enabled autonomous systems. Hamilton-Jacobi (HJ) reachability analysis is a fundamental method for formally ver…
Computing Sound Lower and Upper Bounds on Hamilton-Jacobi Reach-Avoid Value Functions
Ihab Tabbara, Eliya Badr, Hussein Sibai
Hamilton-Jacobi (HJ) reachability analysis is a fundamental tool for the safety verification and control synthesis of nonlinear control systems. Classical HJ reachability analysis…
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 Conservative Neural Control Barrier Functions from Offline Data
Ihab Tabbara, Hussein Sibai
Safety filters, particularly those based on control barrier functions, have gained increased interest as effective tools for safe control of dynamical systems. Existing correct-by-…
Learning Ensembles of Vision-based Safety Control Filters
Ihab Tabbara, Hussein Sibai
Safety filters in control systems correct nominal controls that violate safety constraints. Designing such filters as functions of visual observations in uncertain and complex envi…