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Review of machine learning methods in soft robotics

Author

Listed:
  • Daekyum Kim
  • Sang-Hun Kim
  • Taekyoung Kim
  • Brian Byunghyun Kang
  • Minhyuk Lee
  • Wookeun Park
  • Subyeong Ku
  • DongWook Kim
  • Junghan Kwon
  • Hochang Lee
  • Joonbum Bae
  • Yong-Lae Park
  • Kyu-Jin Cho
  • Sungho Jo

Abstract

Soft robots have been extensively researched due to their flexible, deformable, and adaptive characteristics. However, compared to rigid robots, soft robots have issues in modeling, calibration, and control in that the innate characteristics of the soft materials can cause complex behaviors due to non-linearity and hysteresis. To overcome these limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft sensors, soft actuators, and applications such as soft wearable robots. An analysis of the trends of different machine learning approaches with respect to different types of soft robot applications is presented; in addition to the current limitations in the research field, followed by a summary of the existing machine learning methods for soft robots.

Suggested Citation

  • Daekyum Kim & Sang-Hun Kim & Taekyoung Kim & Brian Byunghyun Kang & Minhyuk Lee & Wookeun Park & Subyeong Ku & DongWook Kim & Junghan Kwon & Hochang Lee & Joonbum Bae & Yong-Lae Park & Kyu-Jin Cho & S, 2021. "Review of machine learning methods in soft robotics," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-24, February.
    • Handle: RePEc:plo:pone00:0246102
    DOI: 10.1371/journal.pone.0246102
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    Cited by:

    1. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    2. Ravil I. Mukhamediev & Yelena Popova & Yan Kuchin & Elena Zaitseva & Almas Kalimoldayev & Adilkhan Symagulov & Vitaly Levashenko & Farida Abdoldina & Viktors Gopejenko & Kirill Yakunin & Elena Muhamed, 2022. "Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges," Mathematics, MDPI, vol. 10(15), pages 1-25, July.

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