94 citations · 100 across the 9 of their papers we have counts for
9 papers
Barrier-Based Test Synthesis for Safety-Critical Systems Subject to Timed Reach-Avoid Specifications
Prithvi Akella, Mohamadreza Ahmadi, Richard M. Murray +1
We propose an adversarial, time-varying test-synthesis procedure for safety-critical systems without requiring specific knowledge of the underlying controller steering the system.…
Synthesizing Reactive Test Environments for Autonomous Systems: Testing Reach-Avoid Specifications with Multi-Commodity Flows
Apurva Badithela, Josefine B. Graebener, Wyatt Ubellacker +3
We study automated test generation for verifying discrete decision-making modules in autonomous systems. We utilize linear temporal logic to encode the requirements on the system u…
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…
Comparative Analysis of Control Barrier Functions and Artificial Potential Fields for Obstacle Avoidance
Andrew Singletary, Karl Klingebiel, Joseph Bourne +3
Artificial potential fields (APFs) and their variants have been a staple for collision avoidance of mobile robots and manipulators for almost 40 years. Its model-independent nature…
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…