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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/80815

    题名: An efficient object recognition and self-localization system for humanoid soccer robot
    作者: Chiang, Jen-Shiun;Hsia, Chih-Hsien;Chang, Shih-Hung;Chang, Wei-Hsuan;Hsu, Hung-Wei;Ho, Meng-Hsuan;Tai, Yi-Che;Li, Chun-Yi
    贡献者: 淡江大學電機工程學系
    关键词: Adaptive Resolution Method;Object Recognition;Real-Time;RoboCup;Self-Localization
    日期: 2010
    上传时间: 2013-03-07 14:01:17 (UTC+8)
    出版者: New York: Institute of Electrical and Electronics Engineers (IEEE)
    摘要: In the RoboCup soccer humanoid league competition, the vision system is used to collect various environment information as the terminal data to finish the functions of object recognition, coordinate establishment, robot localization, robot tactic, barrier avoiding, etc. Thus, a real-time object recognition and high accurate self-localization system of the soccer robot becomes the key technology to improve the performance. In this work we proposed an efficient object recognition and self-localization system for the RoboCup soccer humanoid league rules of the 2009 competition. We proposed two methods : 1) In the object recognition part, the real-time vision-based method is based on the adaptive resolution method (ARM). It can select the most proper resolution for different situations in the competition. ARM can reduce the noises interference and make the object recognition system more robust as well. 2) In the self-localization part, we proposed a new approach, adaptive vision-based self-localization system (AVBSLS), which uses the trigonometric function to find the coarse location of the robot and further adopts the measuring artificial neural network technique to adjust the humanoid robot position adaptively. The experimental results indicate that the proposed system is not easily affected by the light illumination. The object recognition accuracy rate is more than 93% on average and the average frame rate can reach 32 fps (frame per second). It does not only maintain the higher recognition accuracy rate for the high resolution frames, but also increase the average frame rate for about 11 fps compared to the conventional high resolution approach and the average accuracy ratio of the localization is 92.3%.
    關聯: SICE Annual Conference 2010, Proceedings of, pp.2269-2278
    显示于类别:[電機工程學系暨研究所] 會議論文


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