Study on Movement-Pattern Acquisition of Biological Robot using Reinforcement Learning from Evolutional viewpoint
Project/Area Number |
23500275
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Sensitivity informatics/Soft computing
|
Research Institution | Yokohama National University |
Principal Investigator |
YABUTA Tetsuro 横浜国立大学, 工学研究院, 教授 (30323926)
|
Co-Investigator(Kenkyū-buntansha) |
TOYOTA Nozomi 横浜国立大学, 工学研究院, 研究教員 (60547222)
|
Project Period (FY) |
2011 – 2013
|
Project Status |
Completed (Fiscal Year 2013)
|
Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2011: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
Keywords | 強化学習 / 生物型ロボット / 大車輪ロボット / 報酬操作 / ロボットハンド / 人間計測 / 前進行動形態 / Q学習 / 主観報酬 / ハンド / スポーツ型ロボット / 前進歩行形態 / 大車輪運動 |
Research Abstract |
This study clarifies movement-pattern acquisitions of biological robots using reinforcement learning method from evolutionary view point. By comparison between an insect and a reptile, a vertebral column gives essential factor to realize forward movements with small energy consumption. As for a mammal, symmetric condition of its movement-pattern decrease number of forward movement-patterns with small energy consumption. Next, visualization method of motion-pattern with probability clarifies relation between various rewards and success of giant swing for giant swing robot without Markov property. Finally, subjective rewards gives better performance than that of objective rewards because human being can estimate a sequence of movement-pattern form past to future although objective reward is obtained from a present condition.
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Report
(4 results)
Research Products
(35 results)