Long-term human affordance maps

R. Limosani, L. Yoichi Morales, J. Even, F. Ferreri, A. Watanabe, F. Cavallo, P. Dario, N. Hagita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents a work on mapping the use of space by humans in long periods of time. Daily geometric maps with the same coordinate frame were generated with SLAM, and in a similar manner, daily affordance density maps (places people use) were generated with the output of a human tracker running on the robot. The contribution of the paper is two-fold: an approach to detect geometric changes to cluster them in similar geometric configurations and the building of geometric and affordance composite maps on each cluster. This approach avoids the loss of long term retrieved information. Geometric similarity was computed using a normal distance approach on the maps. The analysis was performed on data collected by a mobile robot for a period of 4 months accumulating data equivalent to 70 days. Experimental results show that the system is capable of detecting geometric changes in the environment and clustering similar geometric configurations.

Original languageEnglish
Title of host publicationIROS Hamburg 2015 - Conference Digest
Subtitle of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5748-5754
Number of pages7
ISBN (Electronic)9781479999941
DOIs
Publication statusPublished - 2015 Dec 11
EventIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
Duration: 2015 Sep 282015 Oct 2

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2015-December
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

OtherIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
CountryGermany
CityHamburg
Period15/9/2815/10/2

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Limosani, R., Morales, L. Y., Even, J., Ferreri, F., Watanabe, A., Cavallo, F., Dario, P., & Hagita, N. (2015). Long-term human affordance maps. In IROS Hamburg 2015 - Conference Digest: IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 5748-5754). [7354193] (IEEE International Conference on Intelligent Robots and Systems; Vol. 2015-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2015.7354193