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Flyzone: A testbed for experimenting with aerial drone applications
Politecnico di Milano, Italy; Credit Suisse, Poland.
Politecnico di Milano, Italy.
Politecnico di Milano, Italy.
RISE - Research Institutes of Sweden, ICT, SICS. Politecnico di Milano, Italy.ORCID iD: 0000-0003-4560-9541
2019 (English)In: MobiSys 2019 - Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services, Association for Computing Machinery, Inc , 2019, p. 67-78Conference paper, Published paper (Refereed)
Abstract [en]

FlyZone is a testbed architecture to experiment with aerial drone applications. Unlike most existing drone testbeds that focus on low-level mechanical control, FlyZone offers a high-level API and features geared towards experimenting with application-level functionality. These include the emulation of environment influences, such as wind, and the automatic monitoring of developer-provided safety constraints, for example, to mimic obstacles. We conceive novel solutions to achieve this functionality, including a hardware/software architecture that maximizes decoupling from the main application and a custom visual localization technique expressly designed for testbed operation. We deploy two instances of FlyZone and study performance and effectiveness. We demonstrate that we realistically emulate the environment influence with a positioning error bound by the size of the smallest drone we test, that our localization technique provides a root mean square error of 9.2cm, and that detection of violations to safety constraints happens with a 50ms worst-case latency. We also report on how FlyZone supported developing three real-world drone applications, and discuss a user study demonstrating the benefits of FlyZone compared to drone simulators. 

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2019. p. 67-78
Keywords [en]
Dependability, Drones, Localization, Testbeds, Aircraft detection, Antennas, Application programming interfaces (API), Mean square error, Safety engineering, Automatic monitoring, Environment influence, Localization technique, Root mean square errors, Visual localization, Worst-case latencies
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-40163DOI: 10.1145/3307334.3326106ISBN: 9781450366618 (print)OAI: oai:DiVA.org:ri-40163DiVA, id: diva2:1361278
Conference
17th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2019, 17 June 2019 through 21 June 2019
Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-10-15Bibliographically approved

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Publisher's full texthttps://www2.scopus.com/inward/record.uri?eid=2-s2.0-85069169401&doi=10.1145%2f3307334.3326106&partnerID=40&md5=ae8ea544b5f7e30f6a6a094fd5c09fcd

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Mottola, Luca

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