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Towards visual mapping in industrial environments: a heterogeneous task-specific and saliency driven approach
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-4692-5415
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9477-4044
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-0217-9326
2016 (English)In: 2016 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2016, 5766-5773 p., 7487800Conference paper, Published paper (Refereed)
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Text
Abstract [en]

The highly percipient nature of human mind in avoiding sensory overload is a crucial factor which gives human vision an advantage over machine vision, the latter has otherwise powerful computational resources at its disposal given today’s technology. This stresses the need to focus on methods which extract a concise representation of the environment inorder to approach a complex problem such as visual mapping. This article is an attempt of creating a mapping system, which proposes an architecture that combines task-specific and saliency driven approaches. The proposed method is implemented on a warehouse robot. The proposed solution provide a priority framework which enables an industrial robot to build a concise visual representation of the environment. The method is evaluated on data collected by a RGBD sensor mounted on a fork-lift robot and shows promise for addressing visual mapping problems in industrial environments.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 5766-5773 p., 7487800
Series
IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keyword [en]
Image color analysis, Object detection, Robot sensing systems, Service robots, Training, Visualization
National Category
Engineering and Technology Computer Engineering
Research subject
Computer Science; Computerized Image Analysis; Computer and Systems Science; Computer Engineering; Computer Technology
Identifiers
URN: urn:nbn:se:oru:diva-51234DOI: 10.1109/ICRA.2016.7487800ISI: 000389516204136Scopus ID: 2-s2.0-84977586825ISBN: 978-146738026-3 (print)OAI: oai:DiVA.org:oru-51234DiVA: diva2:945980
Conference
IEEE International Conference on Robotics and Automation (ICRA, Stockholm, Sweden, May 16-21, 2016
Funder
Knowledge Foundation
Available from: 2016-07-04 Created: 2016-07-04 Last updated: 2017-10-18Bibliographically approved

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Siddiqui, J. RafidAndreasson, HenrikDriankov, DimiterLilienthal, Achim J.
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