Sensor fusion-based semantic map building

Joong Tae Park, Jae Bok Song

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

Original languageEnglish
Pages (from-to)277-282
Number of pages6
JournalJournal of Institute of Control, Robotics and Systems
Issue number3
Publication statusPublished - 2011 Mar


  • Door detection
  • Mapping
  • Semantic map
  • Visual feature extraction

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics


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