3D vision based local obstacle avoidance method for humanoid robot

Do Young Lee, Yan Feng Lu, Tae Koo Kang, In Hwan Choi, Myo Taeg Lim

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

7 Citations (Scopus)

Abstract

In this paper, a 3D vision-based local obstacle avoidance system is designed and developed on a humanoid robot so that it can decide avoidance direction and walking motion effectively. We use a panorama environment map using speeded up robust feature (SURF) which is a robust image detector and descriptor to handle the obstacles which exist beyond the field of view. Moreover, we propose an avoidance direction decision method and a fuzzy logic based avoidance motion selection method. The robot decides the avoidance direction and avoidance walking motion for the obstacle by itself under information such as the size of objects and avoidance spaces. The proposed system is applied to the humanoid robot which we have built up with a Time of Flight camera. The results of the experiments show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion.

Original languageEnglish
Title of host publicationICCAS 2012 - 2012 12th International Conference on Control, Automation and Systems
Pages473-475
Number of pages3
Publication statusPublished - 2012
Event2012 12th International Conference on Control, Automation and Systems, ICCAS 2012 - Jeju, Korea, Republic of
Duration: 2012 Oct 172012 Oct 21

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Other

Other2012 12th International Conference on Control, Automation and Systems, ICCAS 2012
CountryKorea, Republic of
CityJeju
Period12/10/1712/10/21

Keywords

  • Humanoid robot
  • Obstacle avoidance
  • avoidance motion selection
  • geographical measurement

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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