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This study presents two control methods for a soft robotic neck, mimicking human neck movements. Both motor position and tip position control using fractional-order controllers demonstrate robust performance under various loads.

Keywords:
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Area of Science:

  • Robotics
  • Biomechanical Engineering
  • Control Systems

Background:

  • Existing soft robotic neck with two Degrees Of Freedom (DOF) enhanced.
  • Mimics human neck flexion, extension, and lateral bending.
  • Utilizes a cable-driven mechanism with a spring-based cervical spine and servomotor-actuated tendons.

Purpose of the Study:

  • To propose and experimentally test two novel control approaches for the improved soft robotic neck.
  • To evaluate the system's robustness under different load configurations.
  • To achieve precise control over desired neck postures.

Main Methods:

  • Developed a 3D-printed soft robotic neck prototype.
  • Implemented a motor position control approach with encoder feedback.
  • Implemented a tip position control approach with Inertial Measurement Unit (IMU) feedback.
  • Applied fractional-order controllers for both approaches.

Main Results:

  • Experimental validation of both motor position and tip position control strategies.
  • Demonstrated the capability to achieve desired postures through servomotor actuation.
  • Confirmed system robustness across various load conditions.

Conclusions:

  • The proposed fractional-order control approaches are effective for the soft robotic neck.
  • The system demonstrates reliable performance and robustness for mimicking human neck movements.
  • The enhanced soft robotic neck offers potential for advanced applications in human-robot interaction and rehabilitation.