Open Access3D Vision-Based Local Path Planning System of a Humanoid Robot for Obstacle Avoidance
Author(s) -
Tae-Koo Kang,
Myo Taeg Lim,
Gwi Tae Park,
Do Hun Kim
Publication year - 2013
Publication title -
journal of electrical engineering and technology/journal of electrical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.226
H-Index - 27
eISSN - 2093-7423
pISSN - 1975-0102
DOI - 10.5370/jeet.2013.8.4.879
Subject(s) - obstacle avoidance , computer vision , humanoid robot , motion planning , artificial intelligence , collision avoidance , obstacle , computer science , robot , path (computing) , mobile robot , engineering , geography , collision , computer security , archaeology , programming language
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.