Obstacle Detection System Based on Stereo Vision and a Structured Light

Kai Peng; Xing Lin Zhou; Ji Guang Liu

doi:10.4028/www.scientific.net/AMR.424-425.1070

Paper Titles

Low Power Wi-Fi(IEEE 802.11) for Mobile Sensing of the Internet of Things of Mine
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Preparation and Analysis of Magnetic Nanoparticles Used as Highly Active Catalysts over a Wide pH Range
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Application and Research of XML Technology in IETM
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Optical Navigation Satellite Constellation Design
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Obstacle Detection System Based on Stereo Vision and a Structured Light
p.1070

The Performance Research of Ceramic Fibers Filtration Composite Material
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FSSS Technical Retrofit of 130T/H All Gas Fired Boiler
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Installation Determination Method of the Combined Wind-Storage System Aiming at Smooth Effects
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Concrete Superplasticizer Prepared from Catalytic Oxidation of Lignosulfonate
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 424-425Obstacle Detection System Based on Stereo Vision...

Obstacle Detection System Based on Stereo Vision and a Structured Light

Abstract:

Obstacle detection is a crucial issue for pilotless device guidance function and it has to be performed with high reliability to avoid any potential collision with the front object. The vision-based obstacle detection systems are regarded perfect for this purpose because they require little on all kind of condition. In this paper, an obstacle detection system using stereo vision sensors and structured light is developed. This system realizes rapid feature matching and high precision measurement distance with the help of structured light, avoiding the time-consuming of the initial corresponding pairs. After the initial detection, the system executes the tracking light strip algorithm for the obstacles. The proposed system can detect a front obstacle in vision field and obtain the size of obstacle. The proposed obstacle detection system is set up and its performance is verified experimentally

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Periodical:

Advanced Materials Research (Volumes 424-425)

Pages:

1070-1074

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.424-425.1070

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Online since:

January 2012

Authors:

Kai Peng, Xing Lin Zhou, Ji Guang Liu

Keywords:

Feature Recognition, Obstacle Detection, Stereo Vision, Structured Light

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