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Bioinspired deformation computational design method for muscle-driven soft robots using MPM.

Ying Yin1, Mo Cheng1, Zhiwei Li1

  • 1School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006 Guangdong, People's Republic of China.

Bioinspiration & Biomimetics
|August 16, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a computational design method for muscle-driven soft robots, enabling them to mimic animal locomotion and achieve desired deformations. The approach effectively generates muscle layouts for bio-inspired robots like snakes and frogs.

Keywords:
bioinspired deformationcomputational designmuscle-drivenphysically-based simulation

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Area of Science:

  • Robotics
  • Bio-inspired Engineering
  • Computational Design

Background:

  • Animals exhibit diverse locomotor forms for environmental adaptation, inspiring research into their deformation and driving mechanisms.
  • Soft robots offer potential for complex movements, but designing their actuation for specific deformations remains challenging.

Purpose of the Study:

  • To propose a computational design method for muscle-driven soft robots that mimics natural animal deformation behaviors.
  • To generate optimal muscle layouts for achieving desired deformations in soft robots.

Main Methods:

  • Utilizing a computational approach to determine muscle-driven layouts based on initial and desired robot shapes.
  • Employing the material point method (MPM) for simulating the coupled and coordinated deformation of soft robotic materials.
  • Developing an efficient search algorithm for muscle layouts corresponding to various deformations.

Main Results:

  • Successfully generated muscle layouts for diverse bio-inspired soft robots, including bionic snakes, frogs, and human faces.
  • Experimental validation showed over 90% overlap between actual and simulated deformations for bionic snake and frog robots.
  • Validated global muscle distributions during motion for bionic snake and human face soft robots through effective simulation.

Conclusions:

  • The proposed computational design method effectively enables muscle-driven soft robots to achieve desired, bio-inspired deformations.
  • The material point method simulation accurately captures the complex deformation behaviors of these soft robots.
  • This approach offers a robust framework for designing versatile bio-inspired soft robots for various applications.