Automated Emergency Landing System for Drones: SafeEYE Project

O. M. Bektash*, Jacob Naundrup Pedersen, Aitor Ramirez Gomez, Anders la Cour-Harbo

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

6 Citations (Scopus)
153 Downloads (Pure)

Abstract

Automated emergency response systems have been the focus for development of more reliable and robust safety systems, from simpler ones to the most complex. For drones, such systems can be designed to allow compliance standards, track safe places for landing and provide an easier development for operational process. Although many works have acknowledged a need for automated response to deal with the increasing drone safety concerns, the literature is still scarce on research incorporating drone operations. Given this outlook, this paper presents the SafeEYE project, which was initiated to develop and commercialise an automated emergency landing system for larger ($>$ 7 kg) drones. The system consists of a small embedded computer, mounted on a drone, that keeps track of safe places to land, or even crash, as well as the health state of the drone. When there is a failure condition, the device can monitor and detect issues using vibration data, select potential landing zones via a convolutional neural network framework and terminate the flight with the least probability of fatalities. This means a significantly reduced risk for automated, typically Beyond Visual Line of Sight, operations. Therefore, SafeEYE has the potential to become a safety enabler for many applications, including farming, inspection, transportation, search and rescue. With the risk mitigation ability, the project aims at achieving formal approval of the Danish authorities and abroad. SafeEYE is planned to be manufactured as a standalone unit, provided first through drone technology suppliers and later to service providers and manufacturers of autopilots.
Original languageEnglish
Title of host publication2020 International Conference on Unmanned Aircraft Systems (ICUAS)
Number of pages9
PublisherIEEE
Publication date6 Oct 2020
Pages1056-1064
Article number9214073
ISBN (Print)978-1-7281-4279-1
ISBN (Electronic)978-1-7281-4278-4
DOIs
Publication statusPublished - 6 Oct 2020
Event 2020 International Conference on Unmanned Aircraft Systems (ICUAS) - Athen, Greece
Duration: 1 Sep 20204 Sep 2020

Conference

Conference 2020 International Conference on Unmanned Aircraft Systems (ICUAS)
Country/TerritoryGreece
CityAthen
Period01/09/202004/09/2020
SeriesInternational Conference on Unmanned Aircraft Systems (ICUAS)
ISSN2575-7296

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