Local environment recognition system using modified surf-based 3d panoramic environment map for obstacle avoidance of a humanoid robot

Tae Koo Kang, In Hwan Choi, Gwi Tae Park, Myo Taeg Lim

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper addresses a local environment recognition system for obstacle avoidance. In vision systems, obstacles that are located beyond the Field of View (FOV) cannot be detected precisely. To deal with the FOV problem, we propose a 3D Panoramic Environment Map (PEM) using a Modified SURF algorithm (MSURF). Moreover, in order to decide the avoidance direction and motion automatically, we also propose a Complexity Measure (CM) and Fuzzy-Logic-based Avoidance Motion Selector (FL-AMS). The CM is utilized to decide an avoidance direction for obstacles. The avoidance motion is determined using FL-AMS, which considers environmental conditions such as the size of obstacles and available space. The proposed system is applied to a humanoid robot built by the authors. The results of the experiment show that the proposed method can be effectively applied to a practical environment.

Original languageEnglish
Article number275
JournalInternational Journal of Advanced Robotic Systems
Volume10
DOIs
Publication statusPublished - 2013 Jun 20

Keywords

  • 3D Panoramic Environment Map
  • Avoidance Motion Selection
  • Complexity Measure
  • Humanoid Robot
  • Obstacle Avoidance

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Science Applications

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