| 研究課題/領域番号 |
22J14202
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| 配分区分 | 補助金 |
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| 研究機関 | 奈良先端科学技術大学院大学 |
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研究代表者 |
Kuo ChengーYu 奈良先端科学技術大学院大学, 先端科学技術研究科, 特別研究員(DC2)
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| 研究期間 (年度) |
2022-04-22 – 2024-03-31
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| キーワード | モデルベース強化学習 / 弾性ロボット / 二脚ロボット / 確率手法 |
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| 研究実績の概要 |
During this year, we utilized model-based reinforcement learning to capture the dynamics of a spring-loaded biped robot. This is significant because the robot's compliancy makes modeling analytic dynamics difficult. Using the learned dynamics, we successfully performed hopping tasks with real-time planning in a simulation environment. These results demonstrate the effectiveness of our approach. Additionally, we have begun hardware implementation, achieving a simple walking task. The performance is expected to significantly improve in the following year.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
In our first year, we made significant progress in researching bipedal robots. We used model-based reinforcement learning to capture their dynamics, which is notable because these robots are difficult to model analytically due to their compliance. Using the learned dynamics, we successfully performed hopping tasks with real-time planning in a simulation environment. We then implemented this approach in hardware and achieved a simple walking task, a crucial step towards testing it in the real world. We are confident and eager to continue making progress in the field of bipedal robots.
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| 今後の研究の推進方策 |
We will conduct hardware testing and modifications, compare our approach with other locomotion methods, and analyze robot performance metrics like speed, energy efficiency, and stability. We will also explore potential applications beyond bipedal robots. Our ultimate goal is to develop efficient bipedal robots for human environments and make a significant impact in this field.
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