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A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system
Rui Yuan1, Qingxi Duan1, Pek Jun Tiw1
1Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, 100871, China.
Nature Communications
|July 8, 2022
Summary
This study introduces a novel neuromorphic perception system using vanadium dioxide (VO2) artificial neurons. This system efficiently encodes multiple physical signals into spikes, enabling applications in e-skin and neurorobotics.
Area of Science:
- Materials Science
- Neuroscience
- Robotics
Background:
- Neuromorphic perception systems offer efficient multi-sensory signal processing but lack suitable hardware.
- Existing artificial neurons struggle with uniformity and adaptability for diverse sensors.
Purpose of the Study:
- To develop a highly efficient, calibratable artificial sensory neuron for neuromorphic systems.
- To address cycle-to-cycle and device-to-device variations in sensory neurons.
- To demonstrate a cross-sensory neuromorphic perception component.
Main Methods:
- Utilized epitaxial vanadium dioxide (VO2) for artificial sensory neurons, enhancing crystalline quality.
- Incorporated a calibration resistor for device-to-device consistency.
- Integrated a scaling resistor for adaptability to various sensor resistance levels.
- Encoded illuminance, temperature, pressure, and curvature signals into spikes.
Main Results:
- Achieved significantly improved cycle-to-cycle uniformity in VO2 neurons.
- Demonstrated device-to-device consistency through calibration.
- Successfully encoded multiple physical signals into spike outputs.
- Classified hand gestures by monitoring finger curvatures.
Conclusions:
- The developed VO2-based sensory neurons overcome key variation issues in neuromorphic hardware.
- This work advances the development of neuromorphic perception systems for applications like electronic skin and neurorobotics.
