94 citations · 98 across the 6 of their papers we have counts for
4 papers · 1 filter
Safety-Critical Controller Verification via Sim2Real Gap Quantification
Prithvi Akella, Wyatt Ubellacker, Aaron D. Ames
The well-known quote from George Box states that: "All models are wrong, but some are useful." To develop more useful models, we quantify the inaccuracy with which a given model re…
A Barrier-Based Scenario Approach to Verify Safety-Critical Systems
Prithvi Akella, Aaron D. Ames
In this letter, we detail our randomized approach to safety-critical system verification. Our method requires limited system data to make a strong verification statement. Specifica…
ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions
Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia +3
Sample-based learning model predictive control (LMPC) strategies have recently attracted attention due to their desirable theoretical properties and their good empirical performanc…
Learning for Safety-Critical Control with Control Barrier Functions
Andrew Taylor, Andrew Singletary, Yisong Yue +1
Modern nonlinear control theory seeks to endow systems with properties of stability and safety, and have been deployed successfully in multiple domains. Despite this success, model…