9 papers
Learning-Based Measurement-Robust Control Barrier Functions for Obstacle Avoidance under State Estimation Error
Nicholas Rober, Yixuan Jia, Jonathan P. How
Safety filters are an effective tool for enforcing constraints in safety-critical systems, but most existing methods assume perfect state information, which is rarely available in…
GUARDIAN: Safety Filtering for Systems with Perception Models Under Adversarial Attack
Nicholas Rober, Alex Rose, Jonathan P. How
Safety filtering is an effective method for enforcing constraints in safety-critical systems, but existing methods typically assume perfect state information. This limitation is es…
DYNUS: Uncertainty-aware Trajectory Planner in Dynamic Unknown Environments
Kota Kondo, Mason Peterson, Nicholas Rober +5
This paper introduces DYNUS, an uncertainty-aware trajectory planner designed for dynamic unknown environments. Operating in such settings presents many challenges -- most notably,…
Safe Autonomy for Uncrewed Surface Vehicles Using Adaptive Control and Reachability Analysis
Karan Mahesh, Tyler M. Paine, Max L. Greene +6
Marine robots must maintain precise control and ensure safety during tasks like ocean monitoring, even when encountering unpredictable disturbances that affect performance. Designi…
Constraint-Aware Refinement for Safety Verification of Neural Feedback Loops
Nicholas Rober, Jonathan P. How
Neural networks (NNs) are becoming increasingly popular in the design of control pipelines for autonomous systems. However, since the performance of NNs can degrade in the presence…
Online Data-Driven Safety Certification for Systems Subject to Unknown Disturbances
Nicholas Rober, Karan Mahesh, Tyler M. Paine +5
Deploying autonomous systems in safety critical settings necessitates methods to verify their safety properties. This is challenging because real-world systems may be subject to di…
A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops
Nicholas Rober, Michael Everett, Songan Zhang +1
As neural networks become more integrated into the systems that we depend on for transportation, medicine, and security, it becomes increasingly important that we develop methods t…
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems
Nicholas Rober, Sydney M. Katz, Chelsea Sidrane +4
As neural networks (NNs) become more prevalent in safety-critical applications such as control of vehicles, there is a growing need to certify that systems with NN components are s…
Backward Reachability Analysis for Neural Feedback Loops
Nicholas Rober, Michael Everett, Jonathan P. How
The increasing prevalence of neural networks (NNs) in safety-critical applications calls for methods to certify their behavior and guarantee safety. This paper presents a backward…