| KEYWORD |
Area Ingegneria
Slimmable Neural Networks for Perception aboard Nano-Drones
Tesi all'estero
Parole chiave APPRENDIMENTO PROFONDO, BASSO CONSUMO, DRONI, EFFICIENZA ENERGETICA, INTELLIGENZA ARTIFICIALE, MICROCONTROLLORI, RETI NEURALI CONVOLUZIONALI, RETI NEURALI PROFONDE, ROBOTICA, SISTEMI EMBEDDED, UAV
Riferimenti DANIELE JAHIER PAGLIARI
Riferimenti esterni Dr. Marco Levorato (UC Irvine), Dr. Alessio Burrello (Politecnico di Torino), Dr. Beatrice Alessandra Motetti (Politecnico di Torino)
Gruppi di ricerca DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ELECTRONIC DESIGN AUTOMATION - EDA, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA
Tipo tesi RICERCA, SPERIMENTALE, SVILUPPO SW
Descrizione If interested in this project, please write me an email attaching your CV with a transcript of your exam scores.
This project considers the task of perception by means of deep neural networks deployed aboard nano-drones. The constrained sensory and computational capacities provided within the power constraints on these tiny robotic platforms (drones with a diameter of approximately 10 cm) imply complex challenges for the real-time execution of deep learning models onboard. The goal of the thesis is the development of an adaptive perception network, that is able to adjust the amount of computation for the inference conditioned on the complexity of the input frames. In particular, the student will explore the application of approaches based on slimmable neural networks, that allow to adjust the width of the layers dynamically at runtime. After the design and the finalization of the perception network, the second milestone of the project will be the actual deployment of the network on a GAP8 System-on-Chip, the same SoC available on the Crazyflie 2.1 nano-drone to run the onboard intelligence.
Vedi anche screenshot 2024-07-17 at 17.00.04.png https://arxiv.org/abs/1812.08928
Conoscenze richieste Proficiency in Python is required. Familiarity with Deep Learning and the PyTorch library is a plus. Furthermore, experience with C programming is desired.
Note The Thesis is in collaboration with Prof. Marco Levorato in University of California, Irvine (USA).
Scadenza validita proposta 17/07/2025
PROPONI LA TUA CANDIDATURA