Autonomous ramp detection and climbing systems for tracked robot using Kinect sensor

I. Hsum Li, Wei-Yen Wang, Yi Hsing Chien, Nai Hong Fang

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

To detect a ramp and guide a tracked robot to complete the ramp-climbing task in an unknown environment, four tracked robot control modes are proposed in this paper. The modes are the exploration mode, aligning mode, calculating the tilt angle mode, and climbing mode. This self-made tracked robot only equips with a Kinect depth sensor; unfortunately, the sensing depth data, in general, incorporate with measuring uncertainties. To attenuate effects from uncertainties, this paper employs the type-1 fuzzy controller to take responsibility of speed control and direction control, and the interval type-2 fuzzy decision strategy to stabilize unnecessary variations occurred in the moment of switching between the four modes. Finally, experiments of autonomous ramp-climbing illustrate the performance of the proposed control scheme for the tracked robot.

Original languageEnglish
Pages (from-to)452-459
Number of pages8
JournalInternational Journal of Fuzzy Systems
Volume15
Issue number4
Publication statusPublished - 2013 Dec 1

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Keywords

  • Interval type-2 fuzzy decision
  • Ramp detection and climbing system
  • Tracked robot

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computational Theory and Mathematics
  • Artificial Intelligence

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