Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-drones

arXiv:2401.15236v2 Announce Type: replace-cross
Abstract: 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. However, their tiny form factor also brings their major drawback: ultra-constrained memory and processors for the onboard execution of their perception pipelines. Therefore, lightweight deep learning-based approaches are becoming increasingly popular, stressing how computational efficiency and energy-saving are paramount as they can make the difference between a fully working …

abstract arxiv bigger cs.cv cs.lg deep learning drones environments flying form humans low major memory narrow power processors type visual