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A method to segment maps from different modalities using free space layout MAORIS: map of ripples segmentation
Örebro University, School of Science and Technology. (MRO Lab)ORCID iD: 0000-0002-3079-0512
Örebro University, School of Science and Technology. (MRO Lab)ORCID iD: 0000-0001-8658-2985
Örebro University, School of Science and Technology. (MRO Lab)ORCID iD: 0000-0003-0217-9326
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

How to divide floor plans or navigation maps into semantic representations, such as rooms and corridors, is an important research question in fields such as human-robot interaction, place categorization, or semantic mapping. While most works focus on segmenting robot built maps, those are not the only types of map a robot, or its user, can use. We present a method for segmenting maps from different modalities, focusing on robot built maps and hand-drawn sketch maps, and show better results than state of the art for both types.

Our method segments the map by doing a convolution between the distance image of the map and a circular kernel, and grouping pixels of the same value. Segmentation is done by detecting ripple-like patterns where pixel values vary quickly, and merging neighboring regions with similar values.

We identify a flaw in the segmentation evaluation metric used in recent works and propose a metric based on Matthews correlation coefficient (MCC). We compare our results to ground-truth segmentations of maps from a publicly available dataset, on which we obtain a better MCC than the state of the art with 0.98 compared to 0.65 for a recent Voronoi-based segmentation method and 0.70 for the DuDe segmentation method.

We also provide a dataset of sketches of an indoor environment, with two possible sets of ground truth segmentations, on which our method obtains an MCC of 0.56 against 0.28 for the Voronoi-based segmentation method and 0.30 for DuDe.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018. p. 4993-4999
Keywords [en]
map segmentation, free space, layout
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-68421ISI: 000446394503114OAI: oai:DiVA.org:oru-68421DiVA, id: diva2:1237531
Conference
IEEE International Conference on Robotics and Automation (ICRA 2018), Brisbane, Australia, May 21-25, 2018
Funder
EU, Horizon 2020, ICT-23-2014 645101 SmokeBotKnowledge Foundation, 20140220Available from: 2018-08-09 Created: 2018-08-09 Last updated: 2018-10-22Bibliographically approved

Open Access in DiVA

A method to segment maps from different modalities using free space layout MAORIS: map of ripples segmentation(1264 kB)98 downloads
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Type fulltextMimetype application/pdf

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Mielle, MalcolmMagnusson, MartinLilienthal, Achim J.

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf