Affordable robot mapping using omnidirectional vision

Mohammad Bamorovat Abadi; Mohamad Reza Shahabian Alashti; Patrick Holthaus; Catherine Menon; Farshid Amirabdollahian

doi:10.31256/If7Nm5Z

Affordable robot mapping using omnidirectional vision

Mohammad Bamorovat Abadi, Mohamad Reza Shahabian Alashti, Patrick Holthaus, Catherine Menon, Farshid Amirabdollahian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Mapping is a fundamental requirement for robot navigation.In this paper, we introduce a novel visual mapping method that relies solely on a single omnidirectional camera.We present a metric that allows us to generate a map from the input image by using a visual Sonar approach.The combination of the visual sonars with the robot's odometry enables us to determine a relation equation and subsequently generate a map that is suitable for robot navigation.Results based on visual map comparison indicate that our approach is comparable with the established solutions based on RGB-D cameras or laser-based sensors. We now embark on evaluating our accuracy against the established methods.

Original language	English
Title of host publication	4th UKRAS21 Conference: Robotics at home Proceedings
Publisher	EPSRC UK-RAS Network
Pages	29-30
Number of pages	2
DOIs	https://doi.org/10.31256/If7Nm5Z
Publication status	Published - 15 Jul 2021
Event	The 4th UK-RAS Conference for PhD Students & Early-Career Researchers on 'Robotics at Home' - Online, Hatfield, United Kingdom Duration: 2 Jun 2021 → 2 Jun 2021 Conference number: 4 https://www.ukras.org.uk/news-and-events/uk-ras/

Publication series

Name	UKRAS21 Conference: Robotics at home Proceedings
Publisher	EPSRC UK-RAS Network
ISSN (Print)	2516-502X

Conference

Conference	The 4th UK-RAS Conference for PhD Students & Early-Career Researchers on 'Robotics at Home'
Abbreviated title	#UKRAS21
Country/Territory	United Kingdom
City	Hatfield
Period	2/06/21 → 2/06/21
Internet address	https://www.ukras.org.uk/news-and-events/uk-ras/

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10.31256/If7Nm5ZLicence: CC BY

Accepted_Manuscript
© 2021 EPSRC UK-Robotics and Autonomous Systems (UK-RAS) Network. This is an open access conference paper distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
Accepted author manuscript, 883 KBLicence: CC BY

Cite this

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title = "Affordable robot mapping using omnidirectional vision",

abstract = "Mapping is a fundamental requirement for robot navigation.In this paper, we introduce a novel visual mapping method that relies solely on a single omnidirectional camera.We present a metric that allows us to generate a map from the input image by using a visual Sonar approach.The combination of the visual sonars with the robot's odometry enables us to determine a relation equation and subsequently generate a map that is suitable for robot navigation.Results based on visual map comparison indicate that our approach is comparable with the established solutions based on RGB-D cameras or laser-based sensors. We now embark on evaluating our accuracy against the established methods.",

author = "{Bamorovat Abadi}, Mohammad and {Shahabian Alashti}, {Mohamad Reza} and Patrick Holthaus and Catherine Menon and Farshid Amirabdollahian",

note = "{\textcopyright} 2021 EPSRC UK-Robotics and Autonomous Systems (UK-RAS) Network. This is an open access conference paper distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/ ; The 4th UK-RAS Conference for PhD Students & Early-Career Researchers on 'Robotics at Home', #UKRAS21 ; Conference date: 02-06-2021 Through 02-06-2021",

year = "2021",

month = jul,

day = "15",

doi = "10.31256/If7Nm5Z",

language = "English",

series = "UKRAS21 Conference: Robotics at home Proceedings",

publisher = "EPSRC UK-RAS Network",

pages = "29--30",

booktitle = "4th UKRAS21 Conference: Robotics at home Proceedings",

url = "https://www.ukras.org.uk/news-and-events/uk-ras/",

}

Bamorovat Abadi, M, Shahabian Alashti, MR, Holthaus, P , Menon, C & Amirabdollahian, F 2021, Affordable robot mapping using omnidirectional vision. in 4th UKRAS21 Conference: Robotics at home Proceedings. UKRAS21 Conference: Robotics at home Proceedings, EPSRC UK-RAS Network, pp. 29-30, The 4th UK-RAS Conference for PhD Students & Early-Career Researchers on 'Robotics at Home', Hatfield, United Kingdom, 2/06/21. https://doi.org/10.31256/If7Nm5Z

Affordable robot mapping using omnidirectional vision. / Bamorovat Abadi, Mohammad; Shahabian Alashti, Mohamad Reza; Holthaus, Patrick et al.
4th UKRAS21 Conference: Robotics at home Proceedings. EPSRC UK-RAS Network, 2021. p. 29-30 (UKRAS21 Conference: Robotics at home Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Affordable robot mapping using omnidirectional vision

AU - Bamorovat Abadi, Mohammad

AU - Shahabian Alashti, Mohamad Reza

AU - Holthaus, Patrick

AU - Menon, Catherine

AU - Amirabdollahian, Farshid

N1 - Conference code: 4

PY - 2021/7/15

Y1 - 2021/7/15

N2 - Mapping is a fundamental requirement for robot navigation.In this paper, we introduce a novel visual mapping method that relies solely on a single omnidirectional camera.We present a metric that allows us to generate a map from the input image by using a visual Sonar approach.The combination of the visual sonars with the robot's odometry enables us to determine a relation equation and subsequently generate a map that is suitable for robot navigation.Results based on visual map comparison indicate that our approach is comparable with the established solutions based on RGB-D cameras or laser-based sensors. We now embark on evaluating our accuracy against the established methods.

AB - Mapping is a fundamental requirement for robot navigation.In this paper, we introduce a novel visual mapping method that relies solely on a single omnidirectional camera.We present a metric that allows us to generate a map from the input image by using a visual Sonar approach.The combination of the visual sonars with the robot's odometry enables us to determine a relation equation and subsequently generate a map that is suitable for robot navigation.Results based on visual map comparison indicate that our approach is comparable with the established solutions based on RGB-D cameras or laser-based sensors. We now embark on evaluating our accuracy against the established methods.

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DO - 10.31256/If7Nm5Z

M3 - Conference contribution

T3 - UKRAS21 Conference: Robotics at home Proceedings

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BT - 4th UKRAS21 Conference: Robotics at home Proceedings

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Y2 - 2 June 2021 through 2 June 2021

ER -

Affordable robot mapping using omnidirectional vision

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