強化学習の適用による柔軟なマイクロシステムの実現

カテゴリ: 論文誌(論文単位)

グループ名: 【E】センサ・マイクロマシン部門

発行日: 2023/03/01

タイトル(英語): Application of Reinforcement Learning to Realize Highly Flexible Microsystem

著者名: 浮田　芳昭（山梨大学大学院総合研究部），阿部　岳晃（山梨大学大学院総合教育部）

著者名(英語): Yoshiaki Ukita (Graduate Faculty of Interdisciplinary Research, University of Yamanashi), Takaaki Abe (Integrated Graduate School of Medicine, Engineering, and Agricultural Sciences, Graduate School of University of Yamanashi)

キーワード: 強化学習，マイクロフルイディクス_x000D_　　reinforcement learning，microfluidics

要約(英語): We herein report on our recent investigation on the development of flexible control of micro (fluidic) system by the application of machine learning (reinforcement learning). Classical peristaltic micropump is employed as platform of the studies and Q-learning algorism, which is also classical algorism of reinforcement learning, is applied to the system. The acquiring of optimal micropumping behavior and manipulation of microbead in microchannel are demonstrated on the platform. The acquired micropumping sequence realize higher flow rate than typical sequences proposed in earlier studies. It is understood that the unique characteristics of the system are considered to acquire the sequence. The efficient micromanipulation of the microbead is also demonstrated on the same platform, even the microdevice is originally designed for the micropumping. Therefore, it could be concluded that the application of the reinforcement learning to a microsystem could be effective to extend the versatility by bringing out the potential of the system.

本誌: 電気学会論文誌E（センサ・マイクロマシン部門誌） Vol.143 No.3 （2023） 特集：ポストパンデミック時代のバイオ・マイクロシステム

本誌掲載ページ: 37-41 p

原稿種別: 解説／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejsmas/143/3/143_37/_article/-char/ja/