7 papers
KALIKO: Kalman-Implicit Koopman Operator Learning For Prediction of Nonlinear Dynamical Systems
Albert H. Li, Ivan Dario Jimenez Rodriguez, Joel W. Burdick +2
Long-horizon dynamical prediction is fundamental in robotics and control, underpinning canonical methods like model predictive control. Yet, many systems and disturbance phenomena…
Safety-Critical Control with Bounded Inputs: A Closed-Form Solution for Backup Control Barrier Functions
David E. J. van Wijk, Ersin Das, Tamas G. Molnar +2
Verifying the safety of controllers is critical for many applications, but is especially challenging for systems with bounded inputs. Backup control barrier functions (bCBFs) offer…
Safe Navigation under State Uncertainty: Online Adaptation for Robust Control Barrier Functions
Ersin Das, Rahal Nanayakkara, Xiao Tan +4
Measurements and state estimates are often imperfect in control practice, posing challenges for safety-critical applications, where safety guarantees rely on accurate state informa…
AI Space Cortex: An Experimental System for Future Era Space Exploration
Thomas Touma, Ersin Daş, Erica Tevere +9
Our Robust, Explainable Autonomy for Scientific Icy Moon Operations (REASIMO) effort contributes to NASA's Concepts for Ocean worlds Life Detection Technology (COLDTech) program, w…
Minimizing Conservatism in Safety-Critical Control for Input-Delayed Systems via Adaptive Delay Estimation
Yitaek Kim, Ersin Das, Jeeseop Kim +3
Input delays affect systems such as teleoperation and wirelessly autonomous connected vehicles, and may lead to safety violations. One promising way to ensure safety in the presenc…
Zero-Order Control Barrier Functions for Sampled-Data Systems with State and Input Dependent Safety Constraints
Xiao Tan, Ersin Das, Aaron D. Ames +1
We propose a novel zero-order control barrier function (ZOCBF) for sampled-data systems to ensure system safety. Our formulation generalizes conventional control barrier functions…