240 citations · 364 across the 22 of their papers we have counts for
5 papers · 1 filter
DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops
Michael Everett, Rudy Bunel, Shayegan Omidshafiei
Safety certification of data-driven control techniques remains a major open problem. This work investigates backward reachability as a framework for providing collision avoidance g…
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…
Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers
Michael Everett, Golnaz Habibi, Jonathan P. How
Neural Networks (NNs) can provide major empirical performance improvements for robotic systems, but they also introduce challenges in formally analyzing those systems' safety prope…