7 papers
A robust approach to sigma point Kalman filtering
Shenglun Yi, Mattia Zorzi
We propose a robust estimator for nonlinear state-space models and provide a clear interpretation of it as the minimizer of a minimax game. The corresponding maximizer searches for…
An update-resilient Kalman filtering approach
Shenglun Yi, Mattia Zorzi
We propose a new robust filtering paradigm considering the situation in which model uncertainty, described through an ambiguity set, is present only in the observations. We derive…
Distributionally Robust LQG with Kullback-Leibler Ambiguity Sets
Marta Fochesato, Lucia Falconi, Mattia Zorzi +2
The Linear Quadratic Gaussian (LQG) controller is known to be inherently fragile to model misspecifications common in real-world situations. We consider discrete-time partially obs…
Data-driven robust UAV position estimation in GPS signal-challenged environment
Shenglun Yi, Xuebo Jin, Zhengjie Wang +2
In this paper, we consider a position estimation problem for an unmanned aerial vehicle (UAV) equipped with both proprioceptive sensors, i.e. IMU, and exteroceptive sensors, i.e. G…
Identification of Non-causal Graphical Models
Junyao You, Mattia Zorzi
The paper considers the problem to estimate non-causal graphical models whose edges encode smoothing relations among the variables. We propose a new covariance extension problem an…
A kernel-based PEM estimator for forward models
Giulio Fattore, Marco Peruzzo, Giacomo Sartori +1
This paper addresses the problem of learning the impulse responses characterizing forward models by means of a regularized kernel-based Prediction Error Method (PEM). The common ap…