Performance improvement of outdoor localization using elevation moment of inertia (EMOI)

Tae Bum Kwon, Jae Bok Song, Yong Ju Lee

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

Abstract

This research proposes a novel approach to outdoor localization based on map matching. The main map for localization is an elevation map which is a grid map with elevation information on each cell. This research presents an elevation moment of inertia (EMOI) which represents the distribution of elevation around a robot in the elevation map. A robot continues to build a local elevation map using a laser sensor and calculates its EMOI. This EMOI is then compared with the EMOIs for all cells of the given reference elevation map to find a robot pose with respect to the reference map. The experimental results of particle filter-based localization show that the proposed EMOI-based approach can be successfully used for outdoor localization with an elevation map.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages144-147
Number of pages4
Publication statusPublished - 2010
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, Japan
Duration: 2010 Feb 42010 Feb 6

Publication series

NameProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10

Other

Other15th International Symposium on Artificial Life and Robotics, AROB '10
CountryJapan
CityBeppu, Oita
Period10/2/410/2/6

Keywords

  • Elevation map
  • Monte Carlo localization
  • Outdoor localization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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