A neuro-inspired artificial peripheral nervous system for scalable electronic skins

Area of Science:

• Robotics and Artificial Intelligence
• Biomimetic Engineering
• Materials Science

Background:

• The human sense of touch is vital for interaction and manipulation.
• Existing electronic skins face limitations in data transmission speed and wiring complexity.
• Need for advanced tactile sensing in intelligent systems like androids and prosthetics.

Purpose of the Study:

• Introduce the Asynchronously Coded Electronic Skin (ACES) platform.
• Overcome readout latency bottlenecks in large-scale sensor arrays.
• Enable simultaneous thermotactile information transmission with high temporal precision.

Main Methods:

• Developed a neuromimetic architecture for electronic skin.
• Implemented asynchronous event transmission for sensor data.
• Demonstrated prototype arrays with artificial mechanoreceptors.

Main Results:

• ACES achieves constant 1 ms latency for arrays >10,000 sensors.
• Demonstrated ultra-high temporal precision (<60 ns).
• Requires only a single conductor, enabling reconfigurable and damage-robust arrays.

Conclusions:

• ACES platform offers a breakthrough in electronic skin technology.
• Enables rapid, high-fidelity tactile perception for AI-enhanced robots and neuroprosthetics.
• Facilitates dexterous object manipulation and somatosensory perception in unstructured environments.