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Fundamental concepts of reactive control for autonomous drones
RISE - Research Institutes of Sweden, ICT, SICS. Politecnico di Milano, Italy.ORCID iD: 0000-0003-4560-9541
University of Virginia, USA.
2018 (English)In: Communications of the ACM, ISSN 0001-0782, E-ISSN 1557-7317, Vol. 61, no 10, p. 96-104Article in journal (Refereed) Published
Abstract [en]

Autonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a timetriggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing the need to, based on the influence of the environment onto the drone operation. As a result, reactive control can dynamically adapt the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time.

Place, publisher, year, edition, pages
2018. Vol. 61, no 10, p. 96-104
Keywords [en]
Aircraft control, Antennas, Computation theory, Computer circuits, Drones, Human computer interaction, Level control, Mobile computing, Motion control, Quality of service, Application logic, Autonomous operations, End-user applications, Fundamental concepts, Hardware platform, Low level control, Mobile computing systems, Real world experiment, Quality control
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-35979DOI: 10.1145/3264417Scopus ID: 2-s2.0-85054526339OAI: oai:DiVA.org:ri-35979DiVA, id: diva2:1261680
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-03-07Bibliographically approved

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Mottola, Luca

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CiteExportLink to record
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  • apa
  • harvard1
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  • fi-FI
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  • Other locale
More languages
Output format
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