157 citations · 172 across the 6 of their papers we have counts for
6 papers
Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones
Lorenzo Lamberti, Vlad Niculescu, Michał Barcis +4
Pocket-sized autonomous nano-drones can revolutionize many robotic use cases, such as visual inspection in narrow, constrained spaces, and ensure safer human-robot interaction due…
Deep Reinforcement Learning for Combined Coverage and Resource Allocation in UAV-aided RAN-slicing
Lorenzo Bellone, Boris Galkin, Emiliano Traversi +1
Network slicing is a well assessed approach enabling virtualization of the mobile core and radio access network (RAN) in the emerging 5th Generation New Radio. Slicing is of paramo…
A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements
Debashisha Mishra, Enrico Natalizio
As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have gained significant research interest within the wireless networking research community. As soon as nat…
Signal-based self-organization of a chain of UAVs for subterranean exploration
Pierre Laclau, Vladislav Tempez, Franck Ruffier +2
Miniature multi-rotors are promising robots for navigating subterranean networks, but maintaining a radio connection underground is challenging. In this paper, we introduce a distr…
Relative Pose Based Redundancy Removal: Collaborative RGB-D Data Transmission in Mobile Visual Sensor Networks
Xiaoqin Wang, Y. Ahmet Sekercioglu, Tom Drummond +3
The Relative Pose based Redundancy Removal(RPRR) scheme is presented, which has been designed for mobile RGB-D sensor networks operating under bandwidth-constrained operational sce…
A fast ILP-based Heuristic for the robust design of Body Wireless Sensor Networks
Fabio D'Andreagiovanni, Antonella Nardin, Enrico Natalizio
We consider the problem of optimally designing a body wireless sensor network, while taking into account the uncertainty of data generation of biosensors. Since the related min-max…