3D vision-based local path planning system of a humanoid robot for obstacle avoidance

Tae Koo Kang, Myo Taeg Lim, Gwi Tae Park, Dong W. Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


This paper addresses the vision based local path planning system for obstacle avoidance. To handle the obstacles which exist beyond the field of view (FOV), we propose a Panoramic Environment Map (PEM) using the MDGHM-SIFT algorithm. Moreover, we propose a Complexity Measure (CM) and Fuzzy logic-based Avoidance Motion Selection (FAMS) system to enable a humanoid robot to automatically decide its own direction and walking motion when avoiding an obstacle. The CM provides automation in deciding the direction of avoidance, whereas the FAMS system chooses the avoidance path and walking motion, based on environment conditions such as the size of the obstacle and the available space around it. The proposed system was applied to a humanoid robot that we designed. The results of the experiment show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a humanoid robot.

Original languageEnglish
Pages (from-to)879-888
Number of pages10
JournalJournal of Electrical Engineering and Technology
Issue number4
Publication statusPublished - 2013 Jul
Externally publishedYes


  • Avoidance motion selection
  • Complexity measure
  • Humanoid robot
  • Local path planning

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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