4 papers · 1 filter
Training on the Fly: On-device Self-supervised Learning aboard Nano-drones within 20 mW
Elia Cereda, Alessandro Giusti, Daniele Palossi
Miniaturized cyber-physical systems (CPSes) powered by tiny machine learning (TinyML), such as nano-drones, are becoming an increasingly attractive technology. Their small form fac…
Fusing Multi-sensor Input with State Information on TinyML Brains for Autonomous Nano-drones
Luca Crupi, Elia Cereda, Daniele Palossi
Autonomous nano-drones (~10 cm in diameter), thanks to their ultra-low power TinyML-based brains, are capable of coping with real-world environments. However, due to their simplifi…
On-device Self-supervised Learning of Visual Perception Tasks aboard Hardware-limited Nano-quadrotors
Elia Cereda, Manuele Rusci, Alessandro Giusti +1
Sub-\SI{50}{\gram} nano-drones are gaining momentum in both academia and industry. Their most compelling applications rely on onboard deep learning models for perception despite se…
Sim-to-Real Vision-depth Fusion CNNs for Robust Pose Estimation Aboard Autonomous Nano-quadcopter
Luca Crupi, Elia Cereda, Alessandro Giusti +1
Nano-quadcopters are versatile platforms attracting the interest of both academia and industry. Their tiny form factor, i.e., 10 cm diameter, makes them particularly useful in…