| Project/Area Number |
19F19380
|
|---|
| Research Category |
Grant-in-Aid for JSPS Fellows
|
| Allocation Type | Single-year Grants |
|---|
| Section | 外国 |
|---|
| Review Section |
Basic Section 61050:Intelligent robotics-related
|
|---|
| Research Institution | Chuo University |
|---|
Principal Investigator |
新妻 実保子 中央大学, 理工学部, 教授 (10548118)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
VINCZE DAVID 中央大学, 理工学部, 外国人特別研究員
|
|---|
| Project Period (FY) |
2019-11-08 – 2022-03-31
|
| Project Status |
Completed (Fiscal Year 2021)
|
| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 2021: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2020: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2019: ¥400,000 (Direct Cost: ¥400,000)
|
|---|
| Keywords | reinforcement learning / Human-Robot Interaction / multi-agent systems / rule-base reduction / fuzzy rule interpolation / knowledge extraction / fuzzy control / antecedent redundancy / fuzzy rule clustering |
|---|
| Outline of Research at the Start |
本研究では，犬の愛着行動のモデル化及び人-ロボットコミュニケーションにおける有用性について取り組むものである。
このアプローチの最大の課題は，行動のモデル化には動物行動学者による観察と知識が不可欠な点である。ヴィンツェ博士と共同して行う研究は，Q-learningによる強化学習のメカニズムとファジィルール補間を統合することにより，動物行動学者の知識も大量の学習データも必要とせず，自動的にゼロからルールベースを構築し，環境からのフィードバックに基づいてルールベースを構築，収束させ，動物行動学的に抽出されるような行動モデルを自動的に抽出しようとするものである。
|
| Outline of Annual Research Achievements |
In this period the possibility of using multiple agents in the Fuzzy Rule Interpolation-based Reinforcement Learning (FRI-RL) and running them distributed in parallel was investigated. As the FRI-RL knowledge extraction method is inherently sequential, some sub-results can be different in the parallel version, but still providing a sufficient solution. This way the knowledge extraction can be performed much faster, therefore using the method on problems with a high dimension count becomes practical. Also, a possible bridging interface between the behaviour simulation model (Strange Situation Test (SST) realized with an FRI-based fuzzy automaton) and real physical robots have been partly designed and implemented. Experimenting with real physical robots is underway. Furthermore a suitable indoor localization system was constructed and adapted to the needs of the planned Human-Robot Interaction (HRI) scenario. This system is able to easily calibrate the indoor localization system’s virtual coordinate system to the real-world physical coordinate system, which makes our planned HRI experiments possible with real humans and mobile robots. A customized robot behaviour engine and a motion control system was developed to support the proposed artificial Strange Situation Test experiments.
|
| Research Progress Status |
令和3年度が最終年度であるため、記入しない。
|
| Strategy for Future Research Activity |
令和3年度が最終年度であるため、記入しない。
|
