Open Space Attraction Based Navigation in Dark Tunnels for MAVs
12th International Conference, ICVS 2019 Thessaloniki, Greece, September 23–25, 2019 Proceedings
Document identifier: oai:DiVA.org:ltu-76965
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10.1007/978-3-030-34995-0_10Keyword: Engineering and Technology,
Electrical Engineering, Electronic Engineering, Information Engineering,
Control Engineering,
Teknik och teknologier,
Elektroteknik och elektronik,
Reglerteknik,
Depth map estimation,
Open space attraction,
Visual navigation,
Micro Aerial VehiclesPublication year: 2019Relevant Sustainable Development Goals (SDGs):
The SDG label(s) above have been assigned by OSDG.aiAbstract: This work establishes a novel framework for characterizing the open space of featureless dark tunnel environments for Micro Aerial Vehicles (MAVs) navigation tasks. The proposed method leverages the processing of a single camera to identify the deepest area in the scene in order to provide a collision free heading command for the MAV. In the sequel and inspired by haze removal approaches, the proposed novel idea is structured around a single image depth map estimation scheme, without metric depth measurements. The core contribution of the developed framework stems from the extraction of a 2D centroid in the image plane that characterizes the center of the tunnel’s darkest area, which is assumed to represent the open space, while the robustness of the proposed scheme is being examined under varying light/dusty conditions. Simulation and experimental results demonstrate the effectiveness of the proposed method in challenging underground tunnel environments.
Authors
Christoforos Kanellakis
Luleå tekniska universitet; Signaler och system
Other publications
>>
Petros Karvelis
Luleå tekniska universitet; Signaler och system
Other publications
>>
George Nikolakopoulos
Luleå tekniska universitet; Signaler och system
Other publications
>>
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identifier: oai:DiVA.org:ltu-76965
datestamp: 2021-04-19T12:50:17Z
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recordCreationDate: 2019-11-29
identifier:
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10.1007/978-3-030-34995-0_10
2-s2.0-85076963724
titleInfo:
@attributes:
lang: eng
title: Open Space Attraction Based Navigation in Dark Tunnels for MAVs
abstract: This work establishes a novel framework for characterizing the open space of featureless dark tunnel environments for Micro Aerial Vehicles (MAVs) navigation tasks. The proposed method leverages the processing of a single camera to identify the deepest area in the scene in order to provide a collision free heading command for the MAV. In the sequel and inspired by haze removal approaches the proposed novel idea is structured around a single image depth map estimation scheme without metric depth measurements. The core contribution of the developed framework stems from the extraction of a 2D centroid in the image plane that characterizes the center of the tunnel’s darkest area which is assumed to represent the open space while the robustness of the proposed scheme is being examined under varying light/dusty conditions. Simulation and experimental results demonstrate the effectiveness of the proposed method in challenging underground tunnel environments.
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Electrical Engineering Electronic Engineering Information Engineering
Control Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Elektroteknik och elektronik
Reglerteknik
@attributes:
lang: eng
topic: Depth map estimation
@attributes:
lang: eng
topic: Open space attraction
@attributes:
lang: eng
topic: Visual navigation
@attributes:
lang: eng
topic: Micro Aerial Vehicles
@attributes:
lang: swe
authority: ltu
topic: Reglerteknik
genre: Research subject
@attributes:
lang: eng
authority: ltu
topic: Control Engineering
genre: Research subject
language:
languageTerm: eng
genre:
conference/other
ref
note:
Published
3
ISBN för värdpublikation: 978-3-030-34994-3 978-3-030-34995-0
name:
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type: personal
authority: ltu
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Kanellakis
Christoforos
role:
roleTerm: aut
affiliation:
Luleå tekniska universitet
Signaler och system
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chrkan
0000-0001-8870-6718
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Karvelis
Petros
role:
roleTerm: aut
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Luleå tekniska universitet
Signaler och system
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petkar
0000-0002-0483-4868
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authority: ltu
namePart:
Nikolakopoulos
George
role:
roleTerm: aut
affiliation:
Luleå tekniska universitet
Signaler och system
nameIdentifier:
geonik
0000-0003-0126-1897
originInfo:
dateIssued: 2019
publisher: Springer
relatedItem:
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type: host
titleInfo:
title: Computer Vision Systems
subTitle: 12th International Conference ICVS 2019 Thessaloniki Greece September 23–25 2019 Proceedings
part:
extent:
start: 110
end: 119
@attributes:
type: series
titleInfo:
title: Lecture Notes in Computer Science
partNumber: 11754
identifier:
0302-9743
1611-3349
location:
url: http://ltu.diva-portal.org/smash/get/diva2:1374228/FULLTEXT01.pdf
accessCondition: gratis
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form: electronic
typeOfResource: text