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Robust Frequency-Based Structure Extraction
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-9503-0602
Applied Intelligent System Lab (AISLab), Università degli Studi di Milano, Milano, Italy.
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-3788-499X
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0001-8658-2985
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2021 (English)In: 2021 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 2021, p. 1715-1721Conference paper, Published paper (Refereed)
Abstract [en]

State of the art mapping algorithms can produce high-quality maps. However, they are still vulnerable to clutter and outliers which can affect map quality and in consequence hinder the performance of a robot, and further map processing for semantic understanding of the environment. This paper presents ROSE, a method for building-level structure detection in robotic maps. ROSE exploits the fact that indoor environments usually contain walls and straight-line elements along a limited set of orientations. Therefore metric maps often have a set of dominant directions. ROSE extracts these directions and uses this information to segment the map into structure and clutter through filtering the map in the frequency domain (an approach substantially underutilised in the mapping applications). Removing the clutter in this way makes wall detection (e.g. using the Hough transform) more robust. Our experiments demonstrate that (1) the application of ROSE for decluttering can substantially improve structural feature retrieval (e.g., walls) in cluttered environments, (2) ROSE can successfully distinguish between clutter and structure in the map even with substantial amount of noise and (3) ROSE can numerically assess the amount of structure in the map.

Place, publisher, year, edition, pages
IEEE, 2021. p. 1715-1721
Series
IEEE International Conference on Robotics and Automation (ICRA), ISSN 1050-4729, E-ISSN 2577-087X
Keywords [en]
Mapping, semantic understanding, indoor environments
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-97000DOI: 10.1109/ICRA48506.2021.9561381ISI: 000765738801089Scopus ID: 2-s2.0-85118997794ISBN: 9781728190778 (electronic)ISBN: 9781728190785 (print)OAI: oai:DiVA.org:oru-97000DiVA, id: diva2:1633891
Conference
IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021
Projects
ILIAD
Funder
EU, Horizon 2020, 732737Available from: 2022-01-31 Created: 2022-01-31 Last updated: 2022-04-25Bibliographically approved

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Robust Frequency-Based Structure Extraction(1151 kB)162 downloads
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Kucner, Tomasz PiotrLowry, StephanieMagnusson, MartinLilienthal, Achim

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Citation style
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