Demo Abstract: Towards Reliable Obstacle Avoidance for Nano-UAVs
dc.contributor.author
Ostovar, Iman
dc.contributor.author
Niculescu, Vlad
dc.contributor.author
Mueller, Hanna
dc.contributor.author
Polonelli, Tommaso
dc.contributor.author
Magno, Michele
dc.contributor.author
Benini, Luca
dc.date.accessioned
2022-10-03T11:24:28Z
dc.date.available
2022-09-29T02:50:43Z
dc.date.available
2022-10-03T11:24:28Z
dc.date.issued
2022-01
dc.identifier.isbn
978-1-6654-9624-7
en_US
dc.identifier.isbn
978-1-6654-9625-4
en_US
dc.identifier.other
10.1109/IPSN54338.2022.00051
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/573211
dc.description.abstract
Unmanned aerial vehicles (UAVs) are a very active research topic, and especially the nano and micro subclass, characterized by centimeter size and minimal on-board computational capabilities, have gained popularity in recent years. These lightweight platforms provide good agility and movement freedom in indoor environments, but it is still a significant challenge to enable autonomous navigation or basic obstacle avoidance capabilities using standard image sensors, due to the limited computational capabilities that can be hosted on-board. This work demonstrates the possibility of using a new multi-zone Time of Flight (ToF) sensor to enhance autonomous navigation with a significantly lower computational load than most common visual-based solutions. Our system proved reliable (>95%) in-field obstacle avoidance capabilities when flying in indoor environments with dynamic obstacles.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
UAV
en_US
dc.subject
nano-UAV
en_US
dc.subject
obstacle avoidance
en_US
dc.subject
autonomous navigation
en_US
dc.title
Demo Abstract: Towards Reliable Obstacle Avoidance for Nano-UAVs
en_US
dc.type
Other Conference Item
dc.date.published
2022-07-18
ethz.book.title
2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
en_US
ethz.pages.start
501
en_US
ethz.pages.end
502
en_US
ethz.event
21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2022)
en_US
ethz.event.location
Milan, Italy
ethz.event.date
May 4-6, 2022
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.date.deposited
2022-09-29T02:50:49Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-10-03T11:24:29Z
ethz.rosetta.lastUpdated
2024-02-02T18:22:41Z
ethz.rosetta.versionExported
true
ethz.COinS
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