2019 Fiscal Year Final Research Report
Shared Autonomous Mobile Sensor Network Systems for Persistent Environmental Monitoring
| Project/Area Number |
19K21077
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| Project/Area Number (Other) |
18H05903 (2018)
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Multi-year Fund (2019)
Single-year Grants (2018) |
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| Review Section |
0302:Electrical and electronic engineering and related fields
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2018-08-24 – 2020-03-31
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| Keywords | 制御工学 / 協調制御 / モバイルセンサネットワーク / 環境モニタリング |
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| Outline of Final Research Achievements |
This project aimed at (1) proposing position estimation algorithms of ground robots by multi-drones, (2) proposing learning methods for information of environments and coverage control algorithms, (3) proposing persistification algorithms of monitoring by considering battery charge for shared autonomous mobile sensor network systems. On topic (1), we succeeded in deriving theoretical results for dynamical estimation of ground robots’ motion. The result was published in a domestic journal. On topic (2), we proposed coverage control algorithms according to learned information of environments. The results were published in international conferences. On topic (3), we succeeded to propose persistification algorithms of monitoring as planned, and verified the algorithms by experiments. The results were published in international conferences.
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| Free Research Field |
システム制御
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| Academic Significance and Societal Importance of the Research Achievements |
ロボット制御では様々な制約のもと，目的を達成する必要がある．本研究課題では，ロボットの安全性，性能保証，制御の持続化を制約条件として記述し，最適化問題として記述可能であることを明らかにした．また，ロボット制御の場合は実時間性が特に重要であり，実験結果からも本研究課題で提案したアルゴリズムが実時間での適用が十分可能であることを示し，学術的に意義深い結果である．また，環境のモニタリングは重要な社会的課題である．本研究課題はロボット群による環境モニタリングに向けた理論と実験の両面からの取り組みとなっており，社会的意義も大きい結果である．
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