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A Novel Data mining method for next-generation robots

A Novel Data mining method for next-generation robots
下一代机器人的新型数据挖掘方法
批准号:
20500181
负责人:
NAKAMURA Takayuki
金额:
$2.83万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2008
资助国家:
日本
项目状态:
已结题
起止时间:
2008 至 2010

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中文摘要
翻译
在这项研究中,我们挑战了对下一代机器人至关重要的新型建模技术的发展。我们假设我们的建模技术有两个功能。功能1检测建模所需的短数据,通过操作机器人生成建模所需的新数据。函数2是从大量采样数据中只选择建模所需的数据的函数。在利用视觉信息控制三自由度机械臂的过程中,研究了基于核主成分分析的方法,该方法利用非线性映射函数将高维学习数据压缩到低维数据。
英文摘要
In this study, we challenge development of the novel modeling technique that is essential to a next-generation robot. We assume that our modeling technique has two functions. Function 1 detects the data which are short for modeling, and generates new data necessary for modeling by operating a robot. Function 2 is a function to choose only data necessary for modeling from a large amount of sampled data. When we controlled a 3-DOF manipulator using visual information, we examined the method based on the Kernel PCA method which can compress high-dimensional learning data using a non-linear mapping function to the low-dimensional data.
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