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Review of machine learning methods in soft robotics.
Kim, Daekyum; Kim, Sang-Hun; Kim, Taekyoung; Kang, Brian Byunghyun; Lee, Minhyuk; Park, Wookeun; Ku, Subyeong; Kim, DongWook; Kwon, Junghan; Lee, Hochang; Bae, Joonbum; Park, Yong-Lae; Cho, Kyu-Jin; Jo, Sungho.
Afiliação
  • Kim D; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
  • Kim SH; Neuro-Machine Augmented Intelligence Laboratory, School of Computing, KAIST, Daejeon, Korea.
  • Kim T; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
  • Kang BB; Biorobotics Laboratory, Department of Mechanical Engineering, Seoul National University, Seoul, Korea.
  • Lee M; Institute of Advanced Machines and Design, Seoul National University, Seoul, Korea.
  • Park W; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
  • Ku S; Institute of Advanced Machines and Design, Seoul National University, Seoul, Korea.
  • Kim D; Soft Robotics & Bionics Lab, Department of Mechanical Engineering, Seoul National University, Seoul, Korea.
  • Kwon J; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
  • Lee H; Biorobotics Laboratory, Department of Mechanical Engineering, Seoul National University, Seoul, Korea.
  • Bae J; Institute of Advanced Machines and Design, Seoul National University, Seoul, Korea.
  • Park YL; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
  • Cho KJ; Bio-Robotics and Control Laboratory, Department of Mechanical Engineering, UNIST, Ulsan, Korea.
  • Jo S; Soft Robotics Research Center, Seoul National University, Seoul, Korea.
PLoS One ; 16(2): e0246102, 2021.
Article em En | MEDLINE | ID: mdl-33600496
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article