7 papers
Over-Approximating Minimizer Sets of Constrained Convex Programs with Parametric Uncertainty via Reachability Analysis
Brendan Gould, Chih-Yuan Chiu, Antoine P. Leeman +3
We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximati…
VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis
Antoine P. Leeman, Shuyu Zhan, Melanie N. Zeilinger +1
We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction guarantees under calibrated unce…
Robustly Constrained Dynamic Games for Uncertain Nonlinear Dynamics
Shuyu Zhan, Chih-Yuan Chiu, Antoine P. Leeman +1
We propose a novel framework for robust dynamic games with nonlinear dynamics corrupted by state-dependent additive noise, and nonlinear agent-specific and shared constraints. Leve…
Safety Beyond the Training Data: Robust Out-of-Distribution MPC via Conformalized System Level Synthesis
Anutam Srinivasan, Antoine Leeman, Glen Chou
We present a novel framework for robust out-of-distribution planning and control using conformal prediction (CP) and system level synthesis (SLS), addressing the challenge of ensur…
Guaranteed Robust Nonlinear MPC via Disturbance Feedback
Antoine P. Leeman, Johannes Köhler, Melanie N. Zeilinger
Robots must satisfy safety-critical state and input constraints despite disturbances and model mismatch. We introduce a robust model predictive control (RMPC) formulation that is f…
Robust Nonlinear Optimal Control via System Level Synthesis
Antoine P. Leeman, Johannes Köhler, Andrea Zanelli +2
This paper addresses the problem of finite horizon constrained robust optimal control for nonlinear systems subject to norm-bounded disturbances. To this end, the underlying uncert…