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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
wwwgc119: 金币+18, 谢谢 2014-03-17 17:30:38
oven1986: 检索EPI+1, 感谢小木应助，鼓励一下。 2014-03-17 17:40:48
Accession number:
20132116364180
Title:
Direction identification system of garlic clove based on machine vision
Authors:
Chi, Gao1 Email author wwwgc119@163.com; Hui, Gao1 Email author gaohui_l@163.com
Author affiliation: 1 Laiwu Vocational and Technical College, Phoenix northbound High-tech Zone of City Laiwu, Province Shandong, China
Corresponding author:
Chi, G. (wwwgc119@163.com)
Source title:
Telkomnika - Indonesian Journal of Electrical Engineering
Abbreviated source title:
Telkomnika Indonesian J. Elect. Eng.
Volume:
11
Issue:
5
Issue date:
May 2013
Publication year:
2013
Pages:
2323-2329
Language:
English
ISSN:
23024046
E-ISSN:
2087278X
Document type:
Journal article (JA)
Publisher:
Universitas Ahmad Dahlan, Jalan Kapas 9, Semaki, Umbul Harjo,, Yogiakarta, 55165, Indonesia
Abstract:
In order to fulfill the requirements of seeding direction of garlic cloves, the paper proposed a research method of garlic clove direction identification based on machine vision, it expounded the theory of garlic clove direction identification, stated the arithmetic of it, designed the direction identification device of it, then developed the control system of garlic clove direction identification based on machine vision, at last tested the garlic clove direction identification, and the result of the experiment certificated that the rate of garlic clove direction identification could reach to more than 97%, and it demonstrated that the research is of high feasibility and technological values. © 2013 Universitas Ahmad Dahlan.
Number of references:
15
Main heading:
Computer vision
Uncontrolled terms:
Garlic clove - research methods
Classification code:
723.5 Computer Applications
Database:
Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.
Accession number:
20134616987929
Title:
Path control experiment of mobile robot based on supervised learning
Authors:
Chi, Gao1, 2 Email author wwwgc119@163.com; Zhou, Luo Min2; Heng, Zhang1
Author affiliation: 1 Mechanical and Electronic Department of Laiwu Vocational and Technical College, Laiwu, Shandong Province, 271100, China
2 Institute of Advanced Manufacturing and Technology, Hefei Institute of Physical Science, Chinese Academy of Sciences, Changzhou, Jiangsu Province, 213164, China
Corresponding author:
Chi, G. (wwwgc119@163.com)
Source title:
Telkomnika - Indonesian Journal of Electrical Engineering
Abbreviated source title:
Telkomnika Indonesian J. Elect. Eng.
Volume:
11
Issue:
12
Issue date:
December 2013
Publication year:
2013
Pages:
7533-7538
Language:
English
ISSN:
23024046
E-ISSN:
2087278X
Document type:
Journal article (JA)
Publisher:
Universitas Ahmad Dahlan, Jalan Kapas 9, Semaki, Umbul Harjo,, Yogiakarta, 55165, Indonesia
Abstract:
To solve the weak capacity and low control accuracy of the robots which adapt to the complexworking conditions, proposed that a path control method based on the driving experience and supervised learning. According to the slope road geometry characteristics, established the modeling study due toramp pavement path control method and the control structure based on monitoring and self-learning.Made use of the Global Navigation Satellite System did the experiment. The test data illustrates thatwhen the running speed is not greater than 5 m/s, the straight-line trajectory path transverse verticaldeviation within 20cm, which proved that the control method has a high feasibility. © 2013 Universitas Ahmad Dahlan.
Number of references:
15
Main heading:
Supervised learning
Controlled terms:
Experiments - Mobile robots
Uncontrolled terms:
Control accuracy - Control methods - Control structure - Driving experiences - Global Navigation Satellite Systems - Path control methods - Route control - Slope path
Classification code:
731.5 Robotics - 901.3 Engineering Research
Database:
Compendex
Compilation and indexing terms, © 2013 Elsevier Inc. |
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