| Project/Area Number |
20800030
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (Start-up)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Perception information processing/Intelligent robotics
|
|---|
| Research Institution | Nara Institute of Science and Technology |
|---|
Principal Investigator |
MATSUBARA Takamitsu Nara Institute of Science and Technology, 情報科学研究科, 助教 (20508056)
|
|---|
| Project Period (FY) |
2008 – 2009
|
| Project Status |
Completed (Fiscal Year 2009)
|
| Budget Amount *help |
¥3,289,000 (Direct Cost: ¥2,530,000、Indirect Cost: ¥759,000)
Fiscal Year 2009: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2008: ¥1,729,000 (Direct Cost: ¥1,330,000、Indirect Cost: ¥399,000)
|
|---|
| Keywords | ヒューマノイドロボット / 運動学習 / 統計学習 / 能動学習 / 見まね学習 / ヒューマノイド / 個性 / ヒト運動予測 / ガウス過程 / 強化学習 |
|---|
| Research Abstract |
In this research, we developed a novel learning procedure to efficiently learn a compact probabilistic movement primitive models from multiple motion sequences demonstrated by humans. The learned models employ a low dimensional parameter vector which represents the style of motion generated by the model. By modifying the parameter vector, efficient adaptation of the model to unknown environments can be achieved.
|
