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文Direction Identification System of Garlic Clove Based on Machine Vision和文Path Control Experiment of Mobile Robot based on Supervised Learning |
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jssxh
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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. |
7楼2014-03-17 14:35:52