具身认知
计算机视觉
计算机科学
人工智能
图像(数学)
图像传感器
作者
Zhilong He,Hongxiao Duan,Jianmin Zeng,Jie Zhou,Xiaolong Zhong,Zhixin Wu,Shenzhou Ni,Ze D. Jiang,Guangjun Xie,Jung‐Yong Lee,Yi Lu,Yonghong Zeng,B. Zhang,Wu Bin Ying,Zhibin Yang,Zhang Zhang,Gang Liu
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2025-01-03
卷期号:11 (1)
标识
DOI:10.1126/sciadv.ads2834
摘要
Retinomorphic systems that can see, recognize, and respond to real-time environmental information will extend the complexity and range of tasks that an exoskeleton robot can perform to better assist physically disabled people. However, the lack of ultrasensitive, reconfigurable, and large-scale integratable retinomorphic devices and advanced edge-processing algorithms makes it difficult to realize retinomorphic hardware. Here, we report the retinomorphic hardware prototype with a 4096-pixel perovskite image sensor array as core module to endow embodied intelligent vision functionalities. The retinomorphic sensor array, using a one photodetector–one transistor geometry to resemble retinal circuit with broadband, ultrahigh, and reconfigurable photoresponsivities, executes both adaptive imaging with a contrast enhancement of ~620% under a dim-lit intensity of 10 microwatts per square centimeter and an instantaneous one-dimensional feature extraction algorithm to decompose the origin visual scenarios into parsimoniously encoded spatiotemporal information. This retinomorphic system endows embodied intelligence with adaptive imaging, in situ processing, and decision-making capabilities and promises enormous potential for autonomous robot applications.
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