oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
SLAM auto-complete: completing a robot map using an emergency map
Örebro University, School of Science and Technology. (MRO Lab, AASS)ORCID iD: 0000-0002-3079-0512
Örebro University, School of Science and Technology. (MRO Lab, AASS)ORCID iD: 0000-0001-8658-2985
Örebro University, School of Science and Technology. (MRO Lab, AASS)ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology. (MRO Lab, AASS)ORCID iD: 0000-0003-0217-9326
2017 (English)In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), IEEE conference proceedings, 2017, 35-40 p., 8088137Conference paper, Published paper (Refereed)
Abstract [en]

In search and rescue missions, time is an important factor; fast navigation and quickly acquiring situation awareness might be matters of life and death. Hence, the use of robots in such scenarios has been restricted by the time needed to explore and build a map. One way to speed up exploration and mapping is to reason about unknown parts of the environment using prior information. While previous research on using external priors for robot mapping mainly focused on accurate maps or aerial images, such data are not always possible to get, especially indoor. We focus on emergency maps as priors for robot mapping since they are easy to get and already extensively used by firemen in rescue missions. However, those maps can be outdated, information might be missing, and the scales of rooms are typically not consistent.

We have developed a formulation of graph-based SLAM that incorporates information from an emergency map. The graph-SLAM is optimized using a combination of robust kernels, fusing the emergency map and the robot map into one map, even when faced with scale inaccuracies and inexact start poses.

We typically have more than 50% of wrong correspondences in the settings studied in this paper, and the method we propose correctly handles them. Experiments in an office environment show that we can handle up to 70% of wrong correspondences and still get the expected result. The robot can navigate and explore while taking into account places it has not yet seen. We demonstrate this in a test scenario and also show that the emergency map is enhanced by adding information not represented such as closed doors or new walls.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017. 35-40 p., 8088137
Keyword [en]
SLAM, robotics, graph, graph SLAM, emergency map, rescue, exploration, auto complete
Keyword [fr]
SLAM, robotics, graph, graph SLAM, plan de secours, sauvetage, exploration, auto complete
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-62057DOI: 10.1109/SSRR.2017.8088137ISBN: 978-1-5386-3923-8 (electronic)ISBN: 978-1-5386-3924-5 (print)OAI: oai:DiVA.org:oru-62057DiVA: diva2:1155435
Conference
2017 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Projects
EU H2020 project SmokeBot (ICT- 23-2014 645101)
Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Mielle, MalcolmMagnusson, MartinAndreasson, HenrikLilienthal, Achim J.

Search in DiVA

By author/editor
Mielle, MalcolmMagnusson, MartinAndreasson, HenrikLilienthal, Achim J.
By organisation
School of Science and Technology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 39 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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