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No map, no problem: A local sensing approach for navigation in human-made spaces using signs
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-1114-6040
2020 (English)In: IEEE International Conference on Intelligent Robots and Systems, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 6148-6155Conference paper, Published paper (Refereed)
Abstract [en]

Robot navigation in human spaces today largely relies on the construction of precise geometric maps and a global motion plan. In this work, we navigate with only local sensing by using available signage - as designed for humans - in human-made environments such as airports. We propose a formalization of "signage"and define 4 levels of signage that we call complete, fully-specified, consistent and valid. The signage formalization can be used on many space skeletonizations, but we specifically provide an approach for navigation on the medial axis. We prove that we can achieve global completeness guarantees without requiring a global map to plan. We validate with two sets of experiments: (1) with real-world airports and their real signs and (2) real New York City neighborhoods. In (1) we show we can use real-world airport signage to improve on a simple random-walk approach, and we explore augmenting signage to further explore signs' impact on trajectory length. In (2), we navigate in varied sized subsets of New York City to show that, since we only use local sensing, our approach scales linearly with trajectory length rather than freespace area.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. p. 6148-6155
Keywords [en]
Agricultural robots, Airports, Intelligent robots, Navigation, Robot programming, Free spaces, Geometric maps, Global motion, Local sensing, New York city, Robot navigation, Simple random walk, Trajectory length, Air navigation
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-301063DOI: 10.1109/IROS45743.2020.9340813ISI: 000714033803114Scopus ID: 2-s2.0-85102404414OAI: oai:DiVA.org:kth-301063DiVA, id: diva2:1597745
Conference
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020, 24 October 2020 through 24 January 2021
Note

QC 20210927

Available from: 2021-09-27 Created: 2021-09-27 Last updated: 2023-04-05Bibliographically approved

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Pokorny, Florian T.

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CiteExportLink to record
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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