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dc.contributor.author
Foehn, Philipp
dc.contributor.author
Brescianini, Dario
dc.contributor.author
Kaufmann, Elia
dc.contributor.author
Cieslewski, Titus
dc.contributor.author
Gehrig, Mathias
dc.contributor.author
Muglikar, Manasi
dc.contributor.author
Scaramuzza, Davide
dc.contributor.editor
Toussaint, Marc
dc.contributor.editor
Bicchi, Antonio
dc.contributor.editor
Hermans, Tucker
dc.date.accessioned
2020-10-21T13:20:25Z
dc.date.available
2020-10-14T04:06:26Z
dc.date.available
2020-10-21T13:20:25Z
dc.date.issued
2020
dc.identifier.isbn
978-0-9923747-6-1
en_US
dc.identifier.other
10.15607/RSS.2020.XVI.081
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/445824
dc.description.abstract
This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The system has successfully been deployed at the first autonomous drone racing world championship: the 2019 AlphaPilot Challenge. Contrary to traditional drone racing systems, which only detect the next gate, our approach makes use of any visible gate and takes advantage of multiple, simultaneous gate detections to compensate for drift in the state estimate and build a global map of the gates. The global map and drift-compensated state estimate allow the drone to navigate through the race course even when the gates are not immediately visible and further enable to plan a near time-optimal path through the race course in real time based on approximate drone dynamics. The proposed system has been demonstrated to successfully guide the drone through tight race courses reaching speeds up to 8 m/s and ranked second at the 2019 AlphaPilot Challenge.
en_US
dc.language.iso
en
en_US
dc.publisher
Robotics: Science and Systems Foundation
en_US
dc.title
AlphaPilot: Autonomous Drone Racing
en_US
dc.type
Conference Paper
ethz.book.title
Proceedings of Robotics: Science and Systems XVI
en_US
ethz.size
9 p.
en_US
ethz.event
16th Conference on Robotics: Science and Systems (RSS 2020) (virtual)
en_US
ethz.event.location
Corvalis, OR, USA
en_US
ethz.event.date
July 12-16, 2020
en_US
ethz.notes
Due to the Coronavirus (COVID-19) the conference was conducted virtually.
en_US
ethz.identifier.wos
ethz.publication.place
s.l.
en_US
ethz.publication.status
published
en_US
ethz.identifier.url
http://www.roboticsproceedings.org/rss16/p081.html
ethz.date.deposited
2020-10-14T04:06:38Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-10-21T13:20:38Z
ethz.rosetta.lastUpdated
2021-02-15T19:01:47Z
ethz.rosetta.versionExported
true
ethz.COinS
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