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Updated: Sep 21, 2025

The Bionic Clicker Mark I & II
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Bio-Inspired Control System for Fingers Actuated by Multiple SMA Actuators.

George-Iulian Uleru1, Mircea Hulea1, Adrian Burlacu2

  • 1Department of Computer Engineering, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, Romania.

Biomimetics (Basel, Switzerland)
|June 1, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel spiking neural network (SNN) structure for controlling robotic fingers using shape memory alloy (SMA) wires. The SNN enables sequential control of finger motions, mimicking biological neural synergies for enhanced dexterity.

Keywords:
anthropomorphic fingerbiomimetic motionsmultiple SMA actuatorsspiking neural networks

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Area of Science:

  • Robotics
  • Neuroscience
  • Materials Science

Background:

  • Spiking neural networks (SNNs) offer precise control for robotic actuators like shape memory alloy (SMA) wires.
  • Bio-inspired robotic systems, such as anthropomorphic fingers, require simultaneous actuation of multiple joints.
  • The motor cortex's control of muscle groups through neural synergies provides a biological model for complex robotic control.

Purpose of the Study:

  • To develop and present a novel SNN structure capable of controlling sequential finger motions.
  • To investigate the hypothesis that neural synergies can be applied to group neuron activation for robotic actuator control.
  • To enhance the biological plausibility of robotic finger control systems.

Main Methods:

  • Designed an SNN architecture to control a robotic finger actuated by four SMA wires.
  • Implemented sequential activation of neuron groups to drive actuators in a coordinated manner.
  • Compared the performance of the SNN-controlled finger with that controlled by a microcontroller.
  • Developed an electronic circuit to model sensor outputs consistent with SNN control.

Main Results:

  • The SNN-controlled artificial finger demonstrated smooth execution of multiple human index finger motions.
  • The SNN provided effective sequential control, initiating subsequent motions based on sensor feedback.
  • The SNN-driven SMA actuators exhibited comparable or superior performance to microcontroller control.

Conclusions:

  • The developed SNN structure successfully controls complex sequential motions in a bio-inspired robotic finger.
  • This approach offers a biologically plausible method for controlling multi-jointed robotic systems.
  • SNNs represent a promising control strategy for advanced robotic applications requiring precise and coordinated movements.