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Inspiration from Visual Ecology for Advancing Multifunctional Robotic Vision Systems: Bio‐inspired Electronic Eyes and Neuromorphic Image Sensors

神经形态工程学 人工智能 机器人学 仿生学 计算机科学 机器人 人机交互 机器视觉 计算机视觉 感知 人工神经网络 生物 神经科学
作者
Changsoon Choi,Gil Ju Lee,Sehui Chang,Young Min Song,Dae‐Hyeong Kim
出处
期刊:Advanced Materials [Wiley]
卷期号:36 (48): e2412252-e2412252 被引量:74
标识
DOI:10.1002/adma.202412252
摘要

In robotics, particularly for autonomous navigation and human-robot collaboration, the significance of unconventional imaging techniques and efficient data processing capabilities is paramount. The unstructured environments encountered by robots, coupled with complex missions assigned to them, present numerous challenges necessitating diverse visual functionalities, and consequently, the development of multifunctional robotic vision systems has become indispensable. Meanwhile, rich diversity inherent in animal vision systems, honed over evolutionary epochs to meet their survival demands across varied habitats, serves as a profound source of inspirations. Here, recent advancements in multifunctional robotic vision systems drawing inspiration from natural ocular structures and their visual perception mechanisms are delineated. First, unique imaging functionalities of natural eyes across terrestrial, aerial, and aquatic habitats and visual signal processing mechanism of humans are explored. Then, designs and functionalities of bio-inspired electronic eyes are explored, engineered to mimic key components and underlying optical principles of natural eyes. Furthermore, neuromorphic image sensors are discussed, emulating functional properties of synapses, neurons, and retinas and thereby enhancing accuracy and efficiency of robotic vision tasks. Next, integration examples of electronic eyes with mobile robotic/biological systems are introduced. Finally, a forward-looking outlook on the development of bio-inspired electronic eyes and neuromorphic image sensors is provided.
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