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A Convolutional Dynamic-Jerk-Planning Algorithm for Impedance Control of Variable-Stiffness Cable-Driven

Luyang Zhang1, Lihui Jia1, Panpan Yang1

  • 1Shandong Provincial Key Laboratory of Precision Manufacturing and Non-Traditional Machining, School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.

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Summary
This summary is machine-generated.

This study introduces a novel algorithm for controlling cable-driven manipulators, enhancing their stability and stiffness for tasks like satellite capture. The method ensures smoother movements and reduces vibrations, improving operational performance.

Keywords:
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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Space Technology

Background:

  • Cable-driven manipulators offer dexterity and controllable stiffness for space applications like satellite capture.
  • Existing methods struggle with motion planning and stiffness control due to complex coupled relationships.

Purpose of the Study:

  • To develop an effective motion planning and impedance control strategy for variable-stiffness cable-driven manipulators.
  • To address challenges in velocity discontinuity and acceleration shock during manipulator operation.

Main Methods:

  • Designed a variable-stiffness cable-driven manipulator with modular components.
  • Devised a convolutional dynamic-jerk-planning algorithm for smooth velocity control.
  • Implemented position-based impedance control for stiffness optimization.

Main Results:

  • The convolutional dynamic-jerk-planning algorithm significantly improved acceleration smoothness and reduced vibrations.
  • Experimental tests confirmed the manipulator's stable movement and effective vibration reduction.
  • Stiffness control experiments demonstrated ideal variable stiffness capabilities.

Conclusions:

  • The proposed algorithm enables stable and smooth motion for cable-driven manipulators.
  • The developed manipulator exhibits effective variable stiffness control for space applications.
  • This research advances the capabilities of robotic systems for on-orbit servicing.