Explore the words cloud of the AirSens project. It provides you a very rough idea of what is the project "AirSens" about.
The following table provides information about the project.
ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA
|Coordinator Country||Italy [IT]|
|Total cost||164˙203 €|
|EC max contribution||164˙203 € (100%)|
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
|Duration (year-month-day)||from 2018-08-06 to 2020-08-05|
Take a look of project's partnership.
|1||ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA||IT (BOLOGNA)||coordinator||164˙203.00|
|2||THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK||US (ALBANY NY)||partner||0.00|
In recent years, the need to enable location- and map-aware services in GPS-deprived environments has become increasingly important, especially after natural disasters events. At the same time, the possibility to form swarms of mini-robots is a very attractive solution for users’ mobiles positioning and for mapping of position-related physical quantities, not only for outdoor but also for indoor scenarios, e.g., assessing the status of buildings immediately after an earthquake. In this context, unmanned aerial vehicles (UAVs) represent a good choice thanks to their flexibility, reconfigurability and advantageous line-of-sight propagation conditions. Despite UAVs’ potentials for indoor positioning, scholars and professionals have mostly considered and used them only for enabling outdoor applications.
In this perspective, AirSens aims at analyzing the potentialities of swarms of UAVs for high-accuracy tracking and sensing in indoor contexts, by addressing three novel objectives: (1) the assessment of the swarms’ localization performance, even in infrastructure-less scenarios, by deriving the fundamental limits and considering energy-efficient solutions; (2) the investigation of swarms’ mapping capabilities, enhanced by crowd-sensing mechanisms; (3) the design of an information-seeking control for navigation (i.e., where the swarm should navigate to provide reliable position estimates) and formation (i.e., which specific swarm geometry can maximize the positioning performance).
These objectives will be pursued through an innovative combination of theoretical and experimental analyses, possible thanks to the synergy between the researcher and her supervisors, experts in the fields of advanced signal processing (USA) and radio-localization (Italy), which perfectly matches the project vision. AirSens will also enhance the researcher technical and managerial skills thanks to multidisciplinary and ad-hoc training activities.
|year||authors and title||journal||last update|
Anna Guerra, Davide Dardari, Petar M. Djuric
Non-Centralized Navigation for Source Localization by Cooperative UAVs
published pages: , ISSN: , DOI:
Anna Guerra, Francesco Guidi, Davide Dardari
Single-Anchor Localization and Orientation Performance Limits Using Massive Arrays: MIMO vs. Beamforming
published pages: 5241-5255, ISSN: 1536-1276, DOI: 10.1109/TWC.2018.2840136
|IEEE Transactions on Wireless Communications 17/8||2019-11-07|
Francesco Guidi, Andrea Mariani, Anna Guerra, Davide Dardari, Antonio Clemente, Raffaele D\'Errico
Indoor Environment-Adaptive Mapping With Beamsteering Massive Arrays
published pages: 10139-10143, ISSN: 0018-9545, DOI: 10.1109/TVT.2018.2853657
|IEEE Transactions on Vehicular Technology 67/10||2019-11-07|
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