Search Results for author: Fabrizio Schiano

Found 6 papers, 3 papers with code

Data-Driven Analytic Differentiation via High Gain Observers and Gaussian Process Priors

no code implementations27 Oct 2022 Biagio Trimarchi, Lorenzo Gentilini, Fabrizio Schiano, Lorenzo Marconi

The presented paper tackles the problem of modeling an unknown function, and its first $r-1$ derivatives, out of scattered and poor-quality data.

Vision-based Drone Flocking in Outdoor Environments

1 code implementation2 Dec 2020 Fabian Schilling, Fabrizio Schiano, Dario Floreano

We employ a convolutional neural network to detect and localize nearby agents onboard the quadcopters in real-time.

Navigate

SwarmLab: a Matlab Drone Swarm Simulator

1 code implementation6 May 2020 Enrica Soria, Fabrizio Schiano, Dario Floreano

Among the available solutions for drone swarm simulations, we identified a gap in simulation frameworks that allow easy algorithms prototyping, tuning, debugging and performance analysis, and do not require the user to interface with multiple programming languages.

Robotics

UWB-based system for UAV Localization in GNSS-Denied Environments: Characterization and Dataset

2 code implementations9 Mar 2020 Jorge Peña Queralta, Carmen Martínez Almansa, Fabrizio Schiano, Dario Floreano, Tomi Westerlund

We show the viability of this system for autonomous flight of UAVs, and provide open-source methods and data that enable its widespread application even with movable anchor systems.

Robotics Systems and Control Systems and Control

Learning Vision-based Flight in Drone Swarms by Imitation

no code implementations8 Aug 2019 Fabian Schilling, Julien Lecoeur, Fabrizio Schiano, Dario Floreano

Decentralized drone swarms deployed today either rely on sharing of positions among agents or detecting swarm members with the help of visual markers.

Collision Avoidance Imitation Learning +1

Learning Vision-based Cohesive Flight in Drone Swarms

no code implementations3 Sep 2018 Fabian Schilling, Julien Lecoeur, Fabrizio Schiano, Dario Floreano

This paper presents a data-driven approach to learning vision-based collective behavior from a simple flocking algorithm.

Collision Avoidance

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