Gait switching and targeted navigation of microswimmers via deep reinforcement learning
Gait switching and targeted navigation of microswimmers via deep reinforcement learning
复制标题
通过深度强化学习实现微型游泳者的步态切换和定向导航
DOI:
10.1038/s42005-022-00935-x
复制
发表时间:
2022
影响因子:
5.5
通讯作者:
Tsang, Alan C.
中科院分区:
文献类型:
--
作者:
Zou, Zonghao;Liu, Yuexin;Young, Y.-N.;Pak, On Shun;Tsang, Alan C.
Swimming microorganisms switch between locomotory gaits to enable complex navigation strategies such as run-and-tumble to explore their environments and search for specific targets. This ability of targeted navigation via adaptive gait-switching is particularly desirable for the development of smart artificial microswimmers that can perform complex biomedical tasks such as targeted drug delivery and microsurgery in an autonomous manner. Here we use a deep reinforcement learning approach to enable a model microswimmer to self-learn effective locomotory gaits for translation, rotation and combined motions. The Artificial Intelligence (AI) powered swimmer can switch between various locomotory gaits adaptively to navigate towards target locations. The multimodal navigation strategy is reminiscent of gait-switching behaviors adopted by swimming microorganisms. We show that the strategy advised by AI is robust to flow perturbations and versatile in enabling the swimmer to perform complex tasks such as path tracing without being explicitly programmed. Taken together, our results demonstrate the vast potential of these AI-powered swimmers for applications in unpredictable, complex fluid environments.
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DOI:
--
发表时间:
1986
期刊:
影响因子:
--
作者:
M. Balkanski
通讯作者:
M. Balkanski
影响因子:
2.7
作者:
Tsang, Alan Cheng Hou;Tong, Pun Wai;Pak, On Shun
通讯作者:
Pak, On Shun
DOI:
10.1103/physreve.80.021903
发表时间:
2009
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
J. Dunkel;Irwin M. Zaid
通讯作者:
Irwin M. Zaid
影响因子:
8.6
作者:
Kirsty Y. Wan;R. Goldstein
通讯作者:
R. Goldstein
影响因子:
2.7
作者:
Jiao, Yusheng;Ling, Feng;Kanso, Eva
通讯作者:
Kanso, Eva