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Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation

  • 0School of Electrical and Electronic Engineering, Technological University Dublin, Dublin, Ireland.
Bioinspiration & Biomimetics +

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October 28, 2024

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October 28, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study enhances embedded sensor networks for soft robots by using a binary excitation signal. This innovation enables faster data extraction and simplifies hardware, improving robotic navigation in complex environments.

Area Of Science

  • Robotics
  • Sensor Networks
  • Embedded Systems

Background

  • Embedded, flexible, multi-sensor networks offer crucial feedback for soft robots in unstructured environments.
  • Current limitations include significant time delays in data extraction and complex network construction.
  • These challenges hinder the widespread adoption and effectiveness of sensor networks in robotics.

Purpose Of The Study

  • To present a novel enhancement to existing embedded sensor networks.
  • To address the challenges of time delay and complexity in sensor network development.
  • To improve the reliability and efficiency of sensor feedback for soft robots.

Main Methods

  • Modified an existing embedded sensor network by changing the excitation signal to a binary signal.
  • Implemented a proof-of-concept system to demonstrate the enhanced network's capabilities.
  • Utilized a two-wire electrical circuit for simultaneous information extraction from multiple reactive sensors.

Main Results

  • The enhanced system allows for data extraction at rates exceeding 5000 measurements per second.
  • Achieved an average measurement error of less than 2% for self-inductance measurements.
  • Demonstrated the feasibility of using small, inexpensive microcontrollers with the new system.

Conclusions

  • The proposed binary signal enhancement significantly accelerates data extraction from embedded sensor networks.
  • This advancement simplifies hardware requirements, enabling the use of cost-effective microcontrollers.
  • The enhanced sensor network shows great potential for improving soft robot performance in dynamic environments.

Keywords: