Extraction and matching of elevation moment of inertia for elevation map-based localization of an outdoor mobile robot

Tae Bum Kwon, Jae Bok Song, Sin Cheon Kang

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

Original languageEnglish
Pages (from-to)203-210
Number of pages8
JournalJournal of Institute of Control, Robotics and Systems
Volume15
Issue number2
DOIs
Publication statusPublished - 2009 Feb 1

Fingerprint

Moment of inertia
Mobile Robot
Mobile robots
Global positioning system
Robots
Robot
Navigation
Probabilistic Approach
Experiments
Cell

Keywords

  • Feature matching
  • Localization
  • Moment of inertia
  • Outdoor navigation

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics

Cite this

Extraction and matching of elevation moment of inertia for elevation map-based localization of an outdoor mobile robot. / Kwon, Tae Bum; Song, Jae Bok; Kang, Sin Cheon.

In: Journal of Institute of Control, Robotics and Systems, Vol. 15, No. 2, 01.02.2009, p. 203-210.

Research output: Contribution to journalArticle

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