2009 Fiscal Year Final Research Report
Self-organizational imitation learning process through unsegmented human-robot interaction
| Project/Area Number |
20800060
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| Research Category |
Grant-in-Aid for Young Scientists (Start-up)
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| Allocation Type | Single-year Grants |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Ritsumeikan University |
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Principal Investigator |
TANIGUCHI Tadahiro Ritsumeikan University, 情報理工学部, 助教 (80512251)
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| Project Period (FY) |
2008 – 2009
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| Keywords | 模倣学習 / 分節化 / 自己組織化型学習 / 時系列 / 統計的学習理論 / ベイズ |
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| Research Abstract |
In this research, we developed a machine learning method which enables a robot to obtain several unit motions from unsegmented human motion. In the method, the learning architecture reduces the dimensionality of observed time series data using singular vector decomposition, models the output data using Switching AR Model (SARM). After SARM encodes the data to code strings, a keyword extraction method extract unit words from the strings based on minimal description length criteria. The extracted words are revealed to be characteristic unit motions.
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