21 citations · 41 across the 14 of their papers we have counts for
8 papers · 1 filter
Distributionally Robust Planning with Adaptive Control
Astghik Hakobyan, Amaras Nazarians, Aditya Gahlawat +2
Safe operation of autonomous systems requires robustness to both model uncertainty and uncertainty in the environment. We propose DRP-AC, a hierarchical framework fo…
Residual-Aware Distributionally Robust EKF: Absorbing Linearization Mismatch via Wasserstein Ambiguity
Minhyuk Jang, Jungjin Lee, Astghik Hakobyan +2
The extended Kalman filter (EKF) is a cornerstone of nonlinear state estimation, yet its performance is fundamentally limited by noise-model mismatch and linearization errors. We d…
Distributionally Robust Kalman Filter
Minhyuk Jang, Astghik Hakobyan, Insoon Yang
We study state estimation for discrete-time linear stochastic systems under distributional ambiguity in the initial state, process noise, and measurement noise. We propose a noise-…
On the Steady-State Distributionally Robust Kalman Filter
Minhyuk Jang, Astghik Hakobyan, Insoon Yang
State estimation in the presence of uncertain or data-driven noise distributions remains a critical challenge in control and robotics. Although the Kalman filter is the most popula…
Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems
Minhyuk Jang, Astghik Hakobyan, Insoon Yang
This paper presents a novel Wasserstein distributionally robust control and state estimation algorithm for partially observable linear stochastic systems, where the probability dis…
Distributionally Robust Differential Dynamic Programming with Wasserstein Distance
Astghik Hakobyan, Insoon Yang
Differential dynamic programming (DDP) is a popular technique for solving nonlinear optimal control problems with locally quadratic approximations. However, existing DDP methods ar…
Wasserstein Distributionally Robust Control of Partially Observable Linear Stochastic Systems
Astghik Hakobyan, Insoon Yang
Distributionally robust control (DRC) aims to effectively manage distributional ambiguity in stochastic systems. While most existing works address inaccurate distributional informa…
Wasserstein Distributionally Robust Control of Partially Observable Linear Systems: Tractable Approximation and Performance Guarantee
Astghik Hakobyan, Insoon Yang
Wasserstein distributionally robust control (WDRC) is an effective method for addressing inaccurate distribution information about disturbances in stochastic systems. It provides v…