activity
20212024
most citedFlexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems

19 citations · 24 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024★ 1 cited

BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance

Hanna Müller, Victor Kartsch, Michele Magno +1

Nano-drones, distinguished by their agility, minimal weight, and cost-effectiveness, are particularly well-suited for exploration in confined, cluttered and narrow spaces. Recogniz…

cs.RO2023

Fully Onboard Low-Power Localization with Semantic Sensor Fusion on a Nano-UAV using Floor Plans

Nicky Zimmerman, Hanna Müller, Michele Magno +1

Nano-sized unmanned aerial vehicles (UAVs) are well-fit for indoor applications and for close proximity to humans. To enable autonomy, the nano-UAV must be able to self-localize in…

cs.CV2023★ 19 cited

Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems

Julian Moosmann, Hanna Mueller, Nicky Zimmerman +3

This paper deploys and explores variants of TinyissimoYOLO, a highly flexible and fully quantized ultra-lightweight object detection network designed for edge systems with a power…

cs.RO2022★ 4 cited

Robust and Efficient Depth-based Obstacle Avoidance for Autonomous Miniaturized UAVs

Hanna Müller, Vlad Niculescu, Tommaso Polonelli +2

Nano-size drones hold enormous potential to explore unknown and complex environments. Their small size makes them agile and safe for operation close to humans and allows them to na…

cs.RO2021

Fully Onboard AI-powered Human-Drone Pose Estimation on Ultra-low Power Autonomous Flying Nano-UAVs

Daniele Palossi, Nicky Zimmerman, Alessio Burrello +6

Artificial intelligence-powered pocket-sized air robots have the potential to revolutionize the Internet-of-Things ecosystem, acting as autonomous, unobtrusive, and ubiquitous smar…