State Estimation

This paper proposes a resilient input and state estimation method for autonomous vehicles, improving robustness against uncertainties and outliers. Simulations in CARLA validate enhanced estimation accuracy and system resilience.

Presented the DRISE (Distributionally Robust Input and State Estimation) framework at IFAC IAV 2025, enhancing autonomous vehicle state estimation resilience through distributional robustness and moment-based ambiguity sets.