Development of motion learning method for a robot with various sensors in a real environment.
| Project/Area Number |
26730136
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent robotics
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| Research Institution | Osaka University |
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Principal Investigator |
Nakamura Yutaka 大阪大学, 基礎工学研究科, 招へい准教授 (70403334)
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| Research Collaborator |
OKADOME Yuya
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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 |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 知能ロボット / 多様なセンサ / 身体的インタラクション / ロボット / ガウス過程回帰 / 強化学習 / 動作計画 |
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| Outline of Final Research Achievements |
In order for a robot to operate in a real environment, it is inevitable to physically interact with diverse objects including human. Such a robot would face to diverse situation, and it is necessary to integrate various sensory input and take appropriate action based on the observation. For this aim, I developed a reinforcement learning method for a robot where the required sensory input is extracted from multi-modal sensory input and a sampling based roadmap method which considers the confidence of the modelling. I also developed a robot socially interact with the human in a real environment.
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Report
(4 results)
Research Products
(6 results)
