no code implementations • 6 Mar 2024 • Elia Cereda, Manuele Rusci, Alessandro Giusti, Daniele Palossi
Sub-\SI{50}{\gram} nano-drones are gaining momentum in both academia and industry.
no code implementations • 21 Feb 2024 • Luca Crupi, Alessandro Giusti, Daniele Palossi
Relative drone-to-drone localization is a fundamental building block for any swarm operations.
no code implementations • 26 Jan 2024 • Beatrice Alessandra Motetti, Luca Crupi, Mustafa Omer Mohammed Elamin Elshaigi, Matteo Risso, Daniele Jahier Pagliari, Daniele Palossi, Alessio Burrello
Sub-10cm diameter nano-drones are gaining momentum thanks to their applicability in scenarios prevented to bigger flying drones, such as in narrow environments and close to humans.
no code implementations • 7 Jan 2024 • Luca Valente, Alessandro Nadalini, Asif Veeran, Mattia Sinigaglia, Bruno Sa, Nils Wistoff, Yvan Tortorella, Simone Benatti, Rafail Psiakis, Ari Kulmala, Baker Mohammad, Sandro Pinto, Daniele Palossi, Luca Benini, Davide Rossi
To the best of the authors' knowledge, it is the first silicon prototype of a ULP SoC coupling the RV64 and RV32 cores in a heterogeneous host+accelerator architecture fully based on the RISC-V ISA.
no code implementations • 4 Jul 2023 • Elia Cereda, Alessandro Giusti, Daniele Palossi
Palm-sized nano-drones are an appealing class of edge nodes, but their limited computational resources prevent running large deep-learning models onboard.
no code implementations • 3 Mar 2023 • Stefano Bonato, Stefano Carlo Lambertenghi, Elia Cereda, Alessandro Giusti, Daniele Palossi
Precise relative localization is a crucial functional block for swarm robotics.
no code implementations • 3 Mar 2023 • Elia Cereda, Luca Crupi, Matteo Risso, Alessio Burrello, Luca Benini, Alessandro Giusti, Daniele Jahier Pagliari, Daniele Palossi
In this work, we leverage a novel neural architecture search (NAS) technique to automatically identify several Pareto-optimal convolutional neural networks (CNNs) for a visual pose estimation task.
no code implementations • 27 Oct 2021 • Marco Ferri, Dario Mantegazza, Elia Cereda, Nicky Zimmerman, Luca M. Gambardella, Daniele Palossi, Jérôme Guzzi, Alessandro Giusti
We consider the task of visually estimating the pose of a human from images acquired by a nearby nano-drone; in this context, we propose a data augmentation approach based on synthetic background substitution to learn a lightweight CNN model from a small real-world training set.
2 code implementations • 10 May 2019 • Daniele Palossi, Francesco Conti, Luca Benini
Nano-size unmanned aerial vehicles (UAVs), with few centimeters of diameter and sub-10 Watts of total power budget, have so far been considered incapable of running sophisticated visual-based autonomous navigation software without external aid from base-stations, ad-hoc local positioning infrastructure, and powerful external computation servers.
3 code implementations • 4 May 2018 • Daniele Palossi, Antonio Loquercio, Francesco Conti, Eric Flamand, Davide Scaramuzza, Luca Benini
As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average.