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A Radiation-Hardened Neuromorphic Imager with Self-Healing Spiking Pixels and Unified Spiking Neural Network for Space Robotics

Quan Cheng, Qiufeng Li, Zhengke Yang, Zhen Kong, Gaoqiang Niu, Yuan Liang, Jiamin Li, Jeong Hoan Park, Wang Liao, Hiromitsu Awano, Takashi Sato, Longyang Lin, Masanori Hashimoto

Year
2025
Citations
2

Abstract

A radiation-hardened neuromorphic imager prototype is developed for space exploration, featuring a fully spike-based neuromorphic vision system architecture, in-pixel self-healing against radiation-induced damage, and integrated unified spiking neural network (USNN) with adaptive neurons and synapses and contrast enhancement at low-contrast conditions. Self-healing reduces dark current by 6.25× at 14kGy cumulative dose, recovering recognition accuracy by 27.8%. USNN consumes 0.0529 pj/SOP at 5,000 events/s.

Keywords

Neuromorphic engineeringSpiking neural networkArtificial intelligencePixelRoboticsComputer scienceArtificial neural networkSpace (punctuation)Computer visionRobot

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