Project description
Making drones quieter so they can hear where they're going
Multi-rotor aerial vehicles' autonomous navigation and interactions are based on artificial intelligence technologies and visual sensing. But visual navigation can fail in the dark or in direct sunlight. Acoustic sensing can complement or even replace vision navigation. It is less costly, and its energy footprint makes it attractive for small-form-factor aircraft. However, the loud noise generated by the drone propulsion poses a challenge. The EU-funded EARS project aims to develop a pioneering system for actively controlling and shaping the aircraft-produced noise, enabling navigation and interaction tasks through a series of scientific and methodological innovations in modelling or signal processing combined with machine learning.
Objective
"Autonomous multi-rotor aerial vehicles (MAVs) are an emerging technology, which has a large number of current and potential applications in a wide range of industries. These airborne vehicles are becoming growingly autonomous thanks to modern artificial intelligence technologies, with their navigation and interaction capabilities based predominantly on visual sensing. While vision navigation has attracted considerable attention, it suffers from a poor performance in low light, limited field of view, and direct sunlight and is vulnerable to occlusions. Acoustic sensing can complement and even replace vision in many situations, and it also benefits from lower system cost and energy footprint, which is especially important for small form-factor aircraft. While novel acoustic technologies based on phased microphone arrays are making their way into the Internet of Things and home automation markets, their use in MAVs is currently impeded by the strong self-noise generated by the drone propulsion system. Consequently, existing commercial and research aerial platforms have advanced vision capabilities, yet no acoustics. This project targets to change this situation, endowing drones with ""ears"". The proposed research aims at the development of novel machine learning-based algorithms and real-time systems for acoustic-based autonomous mapping, localization, and interaction of MAVs. One of the key ideas of the proposal consists of actively controlling and shaping the aircraft self-noise for the benefit of the navigation and interaction tasks, instead of considering it a harmful nuisance. Our end goal is to demonstrate a flying proof-of-concept system which, to the best of our knowledge, will be the first of its kind. While the primary goal of the project is very specific, achieving it will require a considerable amount of scientific and methodological innovation in modelling, signal processing, and machine learning that we expect to have a significant impact on broad domains."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences internet
- engineering and technology mechanical engineering vehicle engineering aerospace engineering aircraft
- social sciences sociology industrial relations automation
- natural sciences physical sciences acoustics
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics autonomous robots drones
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2019-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3400 KLOSTERNEUBURG
Austria
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.