Semantic classification of mobile robot locations through 2D laser scans

Kaleci B., Senler C. M., Dutağacı H., Parlaktuna O.

INTELLIGENT SERVICE ROBOTICS, vol.13, pp.63-85, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13
  • Publication Date: 2020
  • Doi Number: 10.1007/s11370-019-00295-6
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Psycinfo
  • Page Numbers: pp.63-85
  • Keywords: Place classification, Doorway detection, Semantic labeling, Mobile robots, 2D laser, PLACE CLASSIFICATION, LOCALIZATION, INFORMATION, MAPS
  • Eskisehir Osmangazi University Affiliated: Yes


Previous learning-based methods that rely on 2D laser data to classify indoor robot locations into semantic classes were successful in distinguishing between rooms and corridors. However, the classification accuracy remained low for doorway locations. We propose a semantic place classification method that uses a rule-based doorway detection algorithm followed by a classification scheme that models training data through either K-means clustering or learning vector quantization. We conducted extensive experiments on the Freiburg 79 dataset and compared our method to previous semantic place classification algorithms. The doorway detection algorithm we propose significantly increases the classification accuracy for doorway locations as compared to the state-of-the-art performance. We applied our method, trained on the Freiburg 79 dataset, to Freiburg 52 and ESOGU datasets in order to demonstrate its generalization ability.