Real-time building of a thinning-based topological map

Tae Bum Kwon, Jae Bok Song

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

An accurate and compact map is essential to an autonomous mobile robot system. A topological map, one of the most popular map types, can be used to represent the environment in terms of discrete nodes with edges connecting them. It is usually constructed by Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map by using a thinning algorithm. This algorithm, when combined with the application of the C-obstacle, can easily extract only the meaningful topological information in real-time and is robust to environment change, because this map is extracted from a local grid map generated based on the Bayesian update formula. In this paper, position probability is defined to evaluate the quantitative reliability of the end node extracted by the thinning process. Since the thinning process builds only local topological maps, a global topological map should be constructed by merging local topological maps according to nodes with high position probability. For real and complex environments, experiments showed that the proposed map building method based on the thinning process can accurately build a local topological map in real-time, with which an accurate global topological map can be incrementally constructed.

Original languageEnglish
Pages (from-to)211-220
Number of pages10
JournalIntelligent Service Robotics
Volume1
Issue number3
DOIs
Publication statusPublished - 2008 Jul

Bibliographical note

Funding Information:
Acknowledgments This research was conducted for the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Progams funded by the Ministry of Commerce, Industry and Energy of Korea.

Keywords

  • Thinning algorithm
  • Topological map building

ASJC Scopus subject areas

  • Computational Mechanics
  • Engineering (miscellaneous)
  • Mechanical Engineering
  • Artificial Intelligence

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