activity
20212025
most citedUncertainty-aware data-driven predictive control in a stochastic setting

16 citations · 118 across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

7 papers · 1 filter

eess.SY2022★ 16 cited

Uncertainty-aware data-driven predictive control in a stochastic setting

Valentina Breschi, Marco Fabris, Simone Formentin +1

Data-Driven Predictive Control (DDPC) has been recently proposed as an effective alternative to traditional Model Predictive Control (MPC), in that the same constrained optimizatio…

eess.SY2022★ 2 cited

Distributed Dual Quaternion Based Localization of Visual Sensor Networks

Luca Varotto, Marco Fabris, Giulia Michieletto +1

In this paper we consider the localization problem for a visual sensor network. Inspired by the alternate attitude and position distributed optimization framework discussed in [1],…

eess.SY2022★ 5 cited

On the Distributed Estimation from Relative Measurements: a Graph-Based Convergence Analysis

Marco Fabris, Giulia Michieletto, Angelo Cenedese

For a multi-agent system state estimation resting upon noisy measurements constitutes a problem related to several application scenarios. Adopting the standard least-squares approa…

eess.SY2022★ 8 cited

Optimal Time-Invariant Formation Tracking for a Second-Order Multi-Agent System

Marco Fabris, Angelo Cenedese, John Hauser

Given a multi-agent linear system, we formalize and solve a trajectory optimization problem that encapsulates trajectory tracking, distance-based formation control and input energy…

eess.SY2022★ 4 cited

Distributed Strategies for Dynamic Coverage with Limited Sensing Capabilities

Marco Fabris, Angelo Cenedese

In this work, it is presented the development of a novel distributed algorithm performing robotic coverage, clustering and dispatch around an event in static-obstacle structured en…

eess.SY2022★ 3 cited

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Marco Fabris, Daniel Zelazo

This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle. The objective is to drive autonomously the rel…

eess.SP2022★ 8 cited

Visual Sensor Network Stimulation Model Identification via Gaussian Mixture Model and Deep Embedded Features

Luca Varotto, Marco Fabris, Giulia Michieletto +1

Visual sensor networks (VSNs) constitute a fundamental class of distributed sensing systems, with unique complexity and appealing performance features, which correspondingly bring…