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Low-Cost Distributed Optical Waveguide Shape Sensor Based on WTDM Applied in Bionics.

Kai Sun1,2, Zhenhua Wang1,2, Qimeng Liu1,2

  • 1Zhejiang University-Westlake University Joint Training, Zhejiang University, Hangzhou 310027, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel flexible sensor for bionic robotics using optical waveguide shape sensing. This wavelength and time division multiplexing (WTDM) method accurately measures bending angles, paving the way for advanced robotic applications.

Keywords:
WTDMbionicsdistributed shape sensoroptical waveguide

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Area of Science:

  • Robotics and Artificial Intelligence
  • Materials Science and Engineering
  • Optical Sensing Technologies

Background:

  • Advancements in AI, materials, and manufacturing are driving innovation in bionic robotics.
  • Flexible sensors are crucial for achieving breakthroughs in robotic capabilities.
  • Existing shape sensing technologies often face limitations in cost, complexity, or accuracy.

Purpose of the Study:

  • To introduce a novel distributed optical waveguide shape sensing approach for flexible sensors.
  • To demonstrate a cost-effective experimental validation of the proposed sensing method.
  • To develop a data-driven model for accurate shape demodulation using artificial neural networks.

Main Methods:

  • Utilizing wavelength and time division multiplexing (WTDM) for optical waveguide sensing.
  • Employing color filter blocks within optical waveguides for structural design.
  • Combining optical waveguide transmission loss with controlled light source color and intensity variations.
  • Developing an artificial neural network model for data-driven sensor demodulation.

Main Results:

  • Experimental validation of the proposed WTDM optical waveguide shape sensing approach.
  • Achieved a high correlation coefficient of 0.9134 between predicted and real bending angles within 100 seconds.
  • Introduced a confidence accuracy curve to intuitively represent the data-driven model's performance.

Conclusions:

  • The novel WTDM-based optical waveguide sensor offers a promising solution for flexible sensing in bionic robotics.
  • The data-driven artificial neural network model effectively demodulates shape information with high accuracy.
  • This cost-effective approach has the potential to significantly advance the field of robotic sensing.