Local Environment Recognition System Using Modified SURF-Based 3D Panoramic Environment Map for Obstacle Avoidance of a Humanoid Robot

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...

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Bibliographic Details
Published in:International journal of advanced robotic systems 2013-06, Vol.10 (6)
Main Authors: Kang, Tae-Koo, Choi, In-Hwan, Park, Gwi-Tae, Lim, Myo-Taeg
Format: Article
Language:English
Subjects:
Algorithms
Field of view
Fuzzy logic
Humanoid
Methods
Obstacle avoidance
Planning
R&D
Recognition
Research & development
Robots
Success
Vision systems
Walking
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Summary: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.
ISSN:1729-8806
1729-8814
DOI:10.5772/56552