1 code implementation • 14 May 2024 • Matteo Cederle, Marco Fabris, Gian Antonio Susto
Autonomous intersection management (AIM) poses significant challenges due to the intricate nature of real-world traffic scenarios and the need for a highly expensive centralised server in charge of simultaneously controlling all the vehicles.
no code implementations • 23 Mar 2024 • Matteo Cederle, Luca Vittorio Piron, Marina Ceccon, Federico Chiariotti, Alessandro Fabris, Marco Fabris, Gian Antonio Susto
As Machine Learning grows in popularity across various fields, equity has become a key focus for the AI community.
no code implementations • 22 Dec 2023 • Alessandro Chiuso, Marco Fabris, Valentina Breschi, Simone Formentin
Model Predictive Control (MPC) is a powerful method for complex system regulation, but its reliance on an accurate model poses many limitations in real-world applications.
no code implementations • 23 Jul 2023 • Marco Fabris, Giulio Fattore, Angelo Cenedese
This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dynamics.
no code implementations • 23 Jul 2023 • Marco Fabris, Marco D. Bellinazzi, Andrea Furlanetto, Angelo Cenedese
This paper deals with water management over open-channel networks (OCNs) subject to water height imbalance.
no code implementations • 23 Jun 2023 • Marco Fabris, Daniel Zelazo
This work addresses multi-agent consensus networks where adverse attackers affect the convergence performances of the protocol by manipulating the edge weights.
no code implementations • 23 Apr 2023 • Marco Fabris
Regular ring lattices (RRLs) are defined as peculiar undirected circulant graphs constructed from a cycle graph, wherein each node is connected to pairs of neighbors that are spaced progressively in terms of vertex degree.
no code implementations • 1 Apr 2023 • Valentina Breschi, Alessandro Chiuso, Marco Fabris, Simone Formentin
Model predictive control (MPC) is a control strategy widely used in industrial applications.
no code implementations • 18 Nov 2022 • Valentina Breschi, Marco Fabris, Simone Formentin, Alessandro Chiuso
Data-Driven Predictive Control (DDPC) has been recently proposed as an effective alternative to traditional Model Predictive Control (MPC), in that the same constrained optimization problem can be addressed without the need to explicitly identify a full model of the plant.
no code implementations • 11 Mar 2022 • Luca Varotto, Marco Fabris, Giulia Michieletto, Angelo Cenedese
In this paper we consider the localization problem for a visual sensor network.
no code implementations • 21 Feb 2022 • 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.
no code implementations • 21 Feb 2022 • 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 minimization.
no code implementations • 21 Feb 2022 • 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 environments without relying on metric information.
1 code implementation • 18 Jan 2022 • Luca Varotto, Marco Fabris, Giulia Michieletto, Angelo Cenedese
Visual sensor networks (VSNs) constitute a fundamental class of distributed sensing systems, with unique complexity and appealing performance features, which correspondingly bring in quite active lines of research.
no code implementations • 4 Jan 2022 • Marco Fabris, Daniel Zelazo
This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle.
no code implementations • 6 Aug 2021 • Marco Fabris, Giulia Michieletto, Angelo Cenedese
This work presents a novel general regularized distributed solution for the state estimation problem in networked systems.
no code implementations • 9 Jul 2021 • Marco Fabris, Daniel Zelazo
This work mainly addresses continuous-time multiagent consensus networks where an adverse attacker affects the convergence performances of said protocol.
no code implementations • 21 Mar 2021 • Marco Fabris, Giulia Michieletto, Angelo Cenedese
System state estimation constitutes a key problem in several applications involving multi-agent system architectures.