| Budget Amount *help |
¥18,590,000 (Direct Cost: ¥14,300,000、Indirect Cost: ¥4,290,000)
Fiscal Year 2018: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2017: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2016: ¥10,400,000 (Direct Cost: ¥8,000,000、Indirect Cost: ¥2,400,000)
|
|---|
| Outline of Final Research Achievements |
In this research, we aimed to develop model-based reinforcement learning of assistive strategies for physically-assistive robots with data obtained through physical human-robot interactions. With the key concept of "Learning a practical (sub)optimal strategy from a small amount of data", we developed sample-efficient and model-based reinforcement learning algorithms based on Gaussian processes. Then, we developed a safe-assistive device for a knee joint and conducted learning experiments of assistive strategies for physically-assistive robots with human subjects. The experimental results demonstrated the effectiveness of the proposed approach.
|
