240 citations · 364 across the 22 of their papers we have counts for
8 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…
RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation
Lakshay Sharma, Michael Everett, Donggun Lee +3
A key challenge in fast ground robot navigation in 3D terrain is balancing robot speed and safety. Recent work has shown that 2.5D maps (2D representations with additional 3D infor…
Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments
Xiaoyi Cai, Michael Everett, Lakshay Sharma +2
A key challenge in off-road navigation is that even visually similar terrains or ones from the same semantic class may have substantially different traction properties. Existing wo…
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…