Journal of Bionic Engineering ›› 2023, Vol. 20 ›› Issue (3): 845-857.doi: 10.1007/s42235-022-00320-y

• •    下一篇

Hydrogel and Machine Learning for Soft Robots’ Sensing and Signal Processing: A Review

Shuyu Wang1,2; Zhaojia Sun1   

  1. 1 Department of Control Engineering, Northeastern University, Qinhuangdao 066001, China  2 Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
  • 出版日期:2023-05-10 发布日期:2023-05-10
  • 通讯作者: Shuyu Wang E-mail:vincentwang622@126.com
  • 作者简介:Shuyu Wang1,2; Zhaojia Sun1

Hydrogel and Machine Learning for Soft Robots’ Sensing and Signal Processing: A Review

Shuyu Wang1,2; Zhaojia Sun1   

  1. 1 Department of Control Engineering, Northeastern University, Qinhuangdao 066001, China  2 Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
  • Online:2023-05-10 Published:2023-05-10
  • Contact: Shuyu Wang E-mail:vincentwang622@126.com
  • About author:Shuyu Wang1,2; Zhaojia Sun1

摘要: The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perception, control, and signal processing. Hydrogels and machine learning provide promising solutions to the problems above. This review aims to summarize this recent trend by first assessing the current hydrogel-based sensing and actuation methods applied to soft robots. We outlined the mechanisms of perception in response to various external stimuli. Next, recent achievements of machine learning for soft robots’ sensing data processing and optimization are evaluated. Here we list the strategies for implementing machine learning models from the perspective of applications. Last, we discuss the challenges and future opportunities in perception data processing and soft robots’ high level tasks.

关键词: Soft robots , · Bionic robots , · Machine learning , · Hydrogel sensors , · Deep learning

Abstract: The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perception, control, and signal processing. Hydrogels and machine learning provide promising solutions to the problems above. This review aims to summarize this recent trend by first assessing the current hydrogel-based sensing and actuation methods applied to soft robots. We outlined the mechanisms of perception in response to various external stimuli. Next, recent achievements of machine learning for soft robots’ sensing data processing and optimization are evaluated. Here we list the strategies for implementing machine learning models from the perspective of applications. Last, we discuss the challenges and future opportunities in perception data processing and soft robots’ high level tasks.

Key words: Soft robots , · Bionic robots , · Machine learning , · Hydrogel sensors , · Deep learning