Sampling-guided symbolic control framework under changing environments
Project/Area Number |
21K14191
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 21040:Control and system engineering-related
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Research Institution | National Institute of Advanced Industrial Science and Technology (2022) National Institute of Informatics (2021) |
Principal Investigator |
プルエクプラサート サシニー 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 研究員 (50814795)
|
Project Period (FY) |
2021-04-01 – 2024-03-31
|
Project Status |
Granted (Fiscal Year 2022)
|
Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2023: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2022: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2021: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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Keywords | symbolic control / motion planning / robotics / control theory / temporal logic |
Outline of Research at the Start |
This project aims to develop an efficient symbolic control framework for temporal logic specifications in semi-controlled environments. Symbolic control is a well-known approach to synthesizing a provably correct controller under complex specifications such as temporal logic, but this approach's main limitation is its scalability. We will develop a fast symbolic controller synthesis algorithm by performing samplings as guides for the symbolic abstraction. We will also study motion planning for nonholonomic robots based on the proposed framework.
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Outline of Annual Research Achievements |
During this academic year, there were two main research directions of the project. 1. The first direction is to extend the developed symbolic control framework to control and monitor multi-agent systems, focusing on nonholonomic robots. 2. The second direction is to study a safe learning approach using discrete (symbolic) structures.
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Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The project is progressing smoothly. We are extending the developed symbolic controller synthesis algorithm to multi-agent systems.
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Strategy for Future Research Activity |
For the next academic year, which is the last phase of this research project, we will focus on extending the symbolic control algorithms to applications such as robots. We will perform simulations to demonstrate the effectiveness of the algorithms.
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Report
(2 results)
Research Products
(8 results)