Sensing in Soft Robotics

Chidanand Hegde, Jiangtao Su, Joel Ming Rui Tan, Ke He, Xiaodong Chen, Shlomo Magdassi

Research output: Contribution to journalReview articlepeer-review

Abstract

Soft robotics is an exciting field of science and technology that enables robots to manipulate objects with human-like dexterity. Soft robots can handle delicate objects with care, access remote areas, and offer realistic feedback on their handling performance. However, increased dexterity and mechanical compliance of soft robots come with the need for accurate control of the position and shape of these robots. Therefore, soft robots must be equipped with sensors for better perception of their surroundings, location, force, temperature, shape, and other stimuli for effective usage. This review highlights recent progress in sensing feedback technologies for soft robotic applications. It begins with an introduction to actuation technologies and material selection in soft robotics, followed by an in-depth exploration of various types of sensors, their integration methods, and the benefits of multimodal sensing, signal processing, and control strategies. A short description of current market leaders in soft robotics is also included in the review to illustrate the growing demands of this technology. By examining the latest advancements in sensing feedback technologies for soft robots, this review aims to highlight the potential of soft robotics and inspire innovation in the field.

Original languageAmerican English
Pages (from-to)15277-15307
Number of pages31
JournalACS Nano
Volume17
Issue number16
DOIs
StatePublished - 22 Aug 2023

Keywords

  • actuation mechanisms
  • exosuit
  • flexible/stretchable sensors
  • industry leaders in soft grippers
  • materials for soft robots
  • multimodal sensing
  • prosthetics
  • signal processing
  • soft robotic control
  • soft robots

All Science Journal Classification (ASJC) codes

  • General Engineering
  • General Materials Science
  • General Physics and Astronomy

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