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Bioinspired spiking architecture enables energy constrained touch encoding.

Andrea Ortone1,2, Mariangela Filosa1,2,3, Giacomo Indiveri4

  • 1The BioRobotics Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.

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|January 28, 2026
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Summary
This summary is machine-generated.

This study introduces an artificial tactile system using fiber Bragg grating e-skin and a spiking neural network (SNN) for advanced robotics. The system enhances touch perception and localization, offering a scalable, low-power solution for autonomous systems.

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Area of Science:

  • Robotics and Artificial Intelligence
  • Biomimetic Sensing
  • Neuroscience

Background:

  • The human sense of touch is vital for interaction and object manipulation, relying on distributed mechanoreceptors and efficient neural processing.
  • Current robotic tactile sensing faces challenges in wiring, energy consumption, scalability, and parallel processing.
  • Replicating biological touch capabilities is essential for advancing autonomous systems.

Purpose of the Study:

  • To develop a modular artificial tactile system that overcomes limitations of current robotic sensing solutions.
  • To mimic the early stages of the human somatosensory system for enhanced tactile information processing.
  • To demonstrate a scalable and energetically sustainable solution for touch perception in autonomous systems.

Main Methods:

  • Integration of a Fiber Bragg Grating (FBG)-based electronic skin (e-skin) with a spiking neural network (SNN).
  • Implementation of the SNN on a neuromorphic chip for efficient, low-power computation.
  • Bioinspired connectivity was used to investigate its influence on tactile processing.

Main Results:

  • Achieved up to 10x localization super-resolution and improved localization accuracy by 32% compared to deep learning methods.
  • Demonstrated generalization to multitouch and dynamic tactile conditions.
  • The neuromorphic SNN showed robustness to analog neuron constraints, enabling highly parallel, sub-mWatt computation.

Conclusions:

  • The developed artificial tactile system offers a scalable, energy-efficient solution for touch perception.
  • The system provides mechanistic insights into bioinspired tactile processing.
  • This approach has immediate applications in autonomous systems requiring safe human interaction and operation in dynamic environments.