Depth image based terrain recognition for supervisory control of a hybrid quadruped

Artur Saudabayev, Farabi Kungozhin, Damir Nurseitov, Huseyin Atakan Varol

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

1 Citation (Scopus)

Abstract

This paper presents the depth image based locomotion strategy selection framework for a hybrid mobile robot. Terrain recognizer is a major component of a supervisory controller which classifies depth images into terrain types in real-time and selects different locomotion mode sub-controllers. In order to design the terrain recognizer, a database consisting of five terrain types (uneven, level ground, stair up, stair down and not traversable) is generated. Confidence based filtering is applied to enhance depth image data. The accuracy of the terrain classification for the testing database in five class terrain recognition problem is 96.71%. Real-world experiments conducted in mixed terrain environment evaluate both locomotion and terrain recognition capabilities of the robot in real-time. Experimental results show that a consumer depth camera might serve as an effective instrument for terrain recognition and thus locomotion strategy selection for hybrid robots with multiple locomotion modes.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1532-1537
Number of pages6
ISBN (Print)9781479923991
DOIs
Publication statusPublished - Jan 1 2014
Event2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014 - Istanbul, Turkey
Duration: Jun 1 2014Jun 4 2014

Publication series

NameIEEE International Symposium on Industrial Electronics

Other

Other2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014
CountryTurkey
CityIstanbul
Period6/1/146/4/14

Keywords

  • RGB-Depth camera
  • depth image filtering
  • quadruped robot
  • supervisory control
  • terrain recognition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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  • Cite this

    Saudabayev, A., Kungozhin, F., Nurseitov, D., & Varol, H. A. (2014). Depth image based terrain recognition for supervisory control of a hybrid quadruped. In Proceedings - 2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014 (pp. 1532-1537). [6864842] (IEEE International Symposium on Industrial Electronics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2014.6864842