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20232026
most citedNanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots

29 citations · 81 across the 21 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

eess.IV2023

Quantitative Evaluation of a Multi-Modal Camera Setup for Fusing Event Data with RGB Images

Julian Moosmann, Jakub Mandula, Philipp Mayer +2

Event-based cameras, also called silicon retinas, potentially revolutionize computer vision by detecting and reporting significant changes in intensity asynchronous events, offerin…

cs.CV2023★ 8 cited

Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO

Julian Moosmann, Pietro Bonazzi, Yawei Li +4

Smart glasses are rapidly gaining advanced functions thanks to cutting-edge computing technologies, especially accelerated hardware architectures, and tiny Artificial Intelligence…

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…

physics.med-ph2023

Towards a Novel Ultrasound System Based on Low-Frequency Feature Extraction From a Fully-Printed Flexible Transducer

Marco Giordano, Kirill Keller, Francesco Greco +3

Ultrasound is a key technology in healthcare, and it is being explored for non-invasive, wearable, continuous monitoring of vital signs. However, its widespread adoption in this sc…

eess.SP2023

Skilog: A Smart Sensor System for Performance Analysis and Biofeedback in Ski Jumping

Lukas Schulthess, Thorir Mar Ingolfsson, Marc Nölke +3

In ski jumping, low repetition rates of jumps limit the effectiveness of training. Thus, increasing learning rate within every single jump is key to success. A critical element of…

cs.RO2023★ 29 cited

NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots

Vlad Niculescu, Tommaso Polonelli, Michele Magno +1

Perceiving and mapping the surroundings are essential for enabling autonomous navigation in any robotic platform. The algorithm class that enables accurate mapping while correcting…

cs.RO2023★ 26 cited

Fully Onboard SLAM for Distributed Mapping with a Swarm of Nano-Drones

Carl Friess, Vlad Niculescu, Tommaso Polonelli +2

The use of Unmanned Aerial Vehicles (UAVs) is rapidly increasing in applications ranging from surveillance and first-aid missions to industrial automation involving cooperation wit…