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Performance Optimization for Bionic Robotic Dolphin with Active Variable Stiffness Control.

Di Chen1, Yan Xiong1, Bo Wang1

  • 1State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.

Biomimetics (Basel, Switzerland)
|November 24, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel active variable stiffness control method for robotic dolphins, enhancing swimming speed and efficiency. The approach uses motor torque control to mimic a torsion spring, significantly improving robotic swimmer performance.

Keywords:
performance optimizationrobotic dolphintorque controlvariable stiffness mechanism

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Area of Science:

  • Robotics
  • Biomimetics
  • Control Systems

Background:

  • Aquatic animals modulate body stiffness for efficient swimming.
  • Robotic swimmers struggle with dynamic stiffness adjustment for performance enhancement.

Purpose of the Study:

  • To propose and validate an active variable stiffness control method for a robotic dolphin.
  • To improve robotic swimmer speed and efficiency through dynamic stiffness modulation.

Main Methods:

  • Utilized a motor's torque mode to create a variable stiffness component, mimicking a torsion spring.
  • Developed a dynamic model using the Lagrangian method to analyze the variable stiffness mechanism.
  • Conducted extensive experiments to validate the model and explore stiffness-frequency relationships.

Main Results:

  • Demonstrated effective stiffness adjustment in the robotic dolphin's caudal joint.
  • Achieved a maximum speed of 1.12 body lengths per second, a 0.44 BL/s increase.
  • Improved swimming efficiency by 37% through active stiffness control.

Conclusions:

  • Active stiffness adjustment is crucial for robotic swimmer performance.
  • The proposed torque control method offers a viable approach for enhancing robotic swimmer speed and efficiency.
  • This research provides insights for designing advanced robotic swimmers.