| Project/Area Number |
26330312
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Kansei informatics
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| Research Institution | Akita Prefectural University |
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Principal Investigator |
Madokoro Hirokazu 秋田県立大学, システム科学技術学部, 准教授 (10373218)
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| Co-Investigator(Kenkyū-buntansha) |
佐藤 和人 秋田県立大学, システム科学技術学部, 教授 (80390904)
下井 信浩 秋田県立大学, システム科学技術学部, 教授 (10300542)
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| Research Collaborator |
Istvan Lovani
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 適応共鳴理論 / エピソード記憶 / 人間共生ロボット / コンテクスト / カテゴリマップ / 表情空間 / 分類粒度評価 / 並列動作シミュレーション / 人間共生型ロボット / 搭乗型自律移動ロボット / コンテキスト |
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| Outline of Final Research Achievements |
For this study, we proposed a novel method to create episodic memory adaptively and autonomously based on dynamic diversity of facial expression and its context. We conducted evaluation experiments in an actual environment using our autonomous mobile robot prototype as a platform. The proposed method actualized unsupervised learning for counter propagation networks using labels created using adaptive resonance theory network. The evaluation experiment revealed that real-time generation of facial expression maps and context maps were actualized as episodic memory using our original benchmark dataset.
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