Advanced Intelligent Systems (Nov 2024)

A Novel Variable‐Stiffness Tail Based on Layer‐Jamming for Robotic Fish

  • Zicun Hong,
  • Zhenfeng Wu,
  • Qixin Wang,
  • Jianing Li,
  • Yong Zhong

DOI
https://doi.org/10.1002/aisy.202400189
Journal volume & issue
Vol. 6, no. 11
pp. n/a – n/a

Abstract

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Fish have excellent swimming performance, and one key factor is their ability to autonomously adjust body stiffness, which can help them efficiently swim at different speeds and complex environments. At present, the variable‐stiffness design of robotic fish still suffers from structural complexity, severe deformation, and small variation range, which limits the application of variable‐stiffness theory in robotic fish. In this article, a variable‐stiffness tail is designed based on layer‐jamming for robotic fish, which can conveniently achieve online stiffness adjustment while maintaining the optimal stiffness distribution and the shape is unaffected. A modeling method for the tail is proposed by combining the mechanical characteristics of the layer‐jamming structure with the pseudo‐rigid body model. To validate the performance of the tail, a series of experiments are conducted, which show that the stiffness variation range of the tail is around 10 times, and the accuracy of the model in predicting the kinematics of the tail is also verified. Moreover, the thrust tests demonstrate that stiffness adjustment is beneficial for fish swimming at different frequencies. The proposed variable‐stiffness tail will promote the development of efficient underwater biomimetic robots.

Keywords