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Micro/Nanorobotic Swarms: From Fundamentals to Functionalities.
Law, Junhui; Yu, Jiangfan; Tang, Wentian; Gong, Zheyuan; Wang, Xian; Sun, Yu.
Afiliação
  • Law J; Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada.
  • Yu J; School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China.
  • Tang W; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, Guangdong 518129, China.
  • Gong Z; Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada.
  • Wang X; Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada.
  • Sun Y; Department of Mechanical and Materials Engineering, Queen's University, Kingston, Ontario K7L 3N6, Canada.
ACS Nano ; 17(14): 12971-12999, 2023 Jul 25.
Article em En | MEDLINE | ID: mdl-37432675
ABSTRACT
Swarms, which stem from collective behaviors among individual elements, are commonly seen in nature. Since two decades ago, scientists have been attempting to understand the principles of natural swarms and leverage them for creating artificial swarms. To date, the underlying physics; techniques for actuation, navigation, and control; field-generation systems; and a research community are now in place. This Review reviews the fundamental principles and applications of micro/nanorobotic swarms. The generation mechanisms of the emergent collective behaviors among the micro/nanoagents identified over the past two decades are elucidated. The advantages and drawbacks of different techniques, existing control systems, major challenges, and potential prospects of micro/nanorobotic swarms are discussed.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article