Robot motion generation and navigation: What we can learn from rats
| Project/Area Number |
26330296
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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 |
Intelligent robotics
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| Research Institution | Hosei University (2016)
University of Toyama (2014-2015) |
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Principal Investigator |
CAPI Genci 法政大学, 理工学部, 教授 (20389399)
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| Co-Investigator(Kenkyū-buntansha) |
川原 茂敬 富山大学, 大学院理工学研究部(工学), 教授 (10204752)
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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: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | BMI / 知能ロボット / ニューラルネット / 自律ロボット / Local Field Potential / 人工ニューラルネットワーク / ロボット工学 / 学習 / ラット |
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| Outline of Final Research Achievements |
The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves about the surrounding environmental cues. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors to localize and navigate in the complex environment.
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Report
(4 results)
Research Products
(9 results)
