Incremental probabilistic geometry estimation for robot scene understanding

Louis Kenzo Cahier, Tetsuya Ogata, Hiroshi G. Okuno

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

2 Citations (Scopus)

Abstract

Our goal is to give mobile robots a rich representation of their environment as fast as possible. Current mapping methods such as SLAM are often sparse, and scene reconstruction methods using tilting laser scanners are relatively slow. In this paper, we outline a new method for iterative construction of a geometric mesh using streaming time-of-flight range data. Our results show that our algorithm can produce a stable representation after 6 frames, with higher accuracy than raw time-of-flight data.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3625-3630
Number of pages6
ISBN (Print)9781467314039
DOIs
Publication statusPublished - 2012
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: 2012 May 142012 May 18

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
CountryUnited States
CitySaint Paul, MN
Period12/5/1412/5/18

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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  • Cite this

    Cahier, L. K., Ogata, T., & Okuno, H. G. (2012). Incremental probabilistic geometry estimation for robot scene understanding. In 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 (pp. 3625-3630). [6225343] (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2012.6225343