| 研究課題/領域番号 |
19F19722
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| 研究種目 |
特別研究員奨励費
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| 配分区分 | 補助金 |
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| 応募区分 | 外国 |
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| 審査区分 |
小区分62010:生命、健康および医療情報学関連
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| 研究機関 | お茶の水女子大学 |
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研究代表者 |
オベル加藤 ナタナエル お茶の水女子大学, 基幹研究院, 助教 (10749659)
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| 研究分担者 |
CAZENILLE LEO お茶の水女子大学, 基幹研究院, 外国人特別研究員
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| 研究期間 (年度) |
2019-04-25 – 2021-03-31
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| 研究課題ステータス |
完了 (2020年度)
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| 配分額 *注記 |
2,300千円 (直接経費: 2,300千円)
2020年度: 1,100千円 (直接経費: 1,100千円)
2019年度: 1,200千円 (直接経費: 1,200千円)
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| キーワード | Molecular robotics / Swarm robotics / Molecular programming / Evolutionary robotics / Quality-diversity / MAP-Elites / Biochemical-micro-robots / Surrogate models / Reaction-diffusion |
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| 研究開始時の研究の概要 |
We use evolutionary optimization methods and quality-diversity algorithms to design controllers for a swarm of bio-micro-robots. The robots are made of simple beads coated with DNA, which implements both the controller through reaction-diffusion and an anchoring scheme, allowing self-assembly.
Designing appropriate DNA-based chemical reaction networks to serve as robotic controllers is a challenging problem involving non-linear dynamics and high experimental variability. The algorithms selected for this project will allow us to explore the dynamics and trade-offs available to this approach.
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| 研究実績の概要 |
Our aim was to design controllers for self-organizing swarms of micro-robots with specific collective dynamics emerging from local interactions. In particular, we focused on large robotic swarms with millions micrometer-sized micro-robots composed of sepharose beads controlled through the reaction-diffusion dynamics of DNA strands grafted into the robots. We extended the methodology implemented the previous year to automatically design these DNA-based controllers, by using optimization and quality-diversity algorithms and testing promising solutions in simulations. However this approach was especially computationally expensive, in particular because of the complex reaction-diffusion simulations involved. As such, we presented a new method to improve the computational efficiency of such simulations using GPUs with the CUDA framework (paper "Accelerating the Finite-Element Method for Reaction-Diffusion Simulations on GPUs with CUDA"). Another limitation of our methodology to automatically design robot controllers was that the user previously had to manually provide scores ("feature descriptors") quantifying how diverse the tested solutions were, a typical aspect of quality-diversity algorithms. We described a new methodology to find automatically these diversity scores for a target problem (paper "Ensemble Feature Extraction for Multi-Container Quality-Diversity Algorithms").
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| 現在までの達成度 (段落) |
令和2年度が最終年度であるため、記入しない。
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| 今後の研究の推進方策 |
令和2年度が最終年度であるため、記入しない。
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