Seminar Details
2026-05-05 (14:00) : Designing Provably Safe Autonomous Systems Under Uncertainty
At Euler building (room A.002)
Duration: 60 minutes
Organized by Mathematical Engineering
Abstract :
The deployment of autonomous aerial and ground vehicles in real-world environments presents fundamental challenges in ensuring safety and resilience under uncertainty. As autonomy increases and human oversight diminishes, we must develop formal methods that provide mathematical guarantees on system behavior in the face of stochastic disturbances and environmental variability.
This talk presents recent advances in data-driven verification and control synthesis for both linear and nonlinear stochastic models. We differentiate between abstraction-based and abstraction-free approaches and show how approximate stochastic simulation relations can be used to quantify abstractions, enabling scalable formal verification of systems with uncertainty. Building on this foundation, we address control synthesis for autonomy via a tight integration of symbolic logic, stochastic formal methods, and uncertainty quantification — paving the way toward interacting autonomous systems that are not only capable, but also provably safe.