6 papers · 1 filter
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…
Learning Neural Control Barrier Functions from Expert Demonstrations using Inverse Constraint Learning
Yuxuan Yang, Hussein Sibai
Safety is a fundamental requirement for autonomous systems operating in critical domains. Control barrier functions (CBFs) have been used to design safety filters that minimally al…
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 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…