1 citations · 1 across the 6 of their papers we have counts for
11 papers · 1 filter
Learning Certified Neural Network Controllers Using Contraction and Interval Analysis
Akash Harapanahalli, Samuel Coogan, Alexander Davydov
We present a novel framework that jointly trains a neural network controller and a neural Riemannian metric with rigorous closed-loop contraction guarantees using formal bound prop…
linrax: A JAX Compatible, Simplex Method Linear Program Solver
Brendan Gould, Akash Harapanahalli, Samuel Coogan
We present linrax, the first simplex based linear program (LP) solver compatible with the JAX ecosystem. In many control algorithms, LPs are often automatically generated and frequ…
Output Feedback Backup Control Barrier Functions: Safety Guarantees Under Input Bounds and State Estimation Error
David E. J. van Wijk, Tamas G. Molnar, Samuel Coogan +3
Guaranteeing the safety of controllers is vital for real-world applications, but is markedly difficult when the states are not perfectly known and when the control inputs are bound…
Differentiable Invariant Sets for Hybrid Limit Cycles with Application to Legged Robots
Varun Madabushi, Akash Harapanahalli, Samuel Coogan +1
For hybrid systems exhibiting periodic behavior, analyzing the invariant set containing the limit cycle is a natural way to study the robustness of the closed-loop system. However,…
Uncertainty Estimators for Robust Backup Control Barrier Functions
David E. J. van Wijk, Ersin Das, Anil Alan +5
Designing safe controllers is crucial and notoriously challenging for input-constrained safety-critical control systems. Backup control barrier functions offer an approach for the…
Automatic and Scalable Safety Verification using Interval Reachability with Subspace Sampling
Brendan Gould, Akash Harapanahalli, Samuel Coogan
Interval refinement is a technique for reducing the conservatism of traditional interval based reachability methods by lifting the system to a higher dimension using new auxiliary…