矿视网形状图像传感器用于体内智能视觉.
Zhilong He1, Hongxiao Duan1, Jianmin Zeng1,2
1Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Science advances
|January 3, 2025
概括
这项研究介绍了一种使用矿图像传感器的新型视网形硬件原型. 该系统使机器人能够看到,处理和响应实时视觉数据,以增强体内智能.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 材料科学与工程 材料科学与工程
- 神经科学和生物启发的计算
背景情况:
- 外骨架机器人需要先进的视觉系统来增强人类的协助.
- 目前的视网形态设备缺乏灵敏度,重新配置性和大规模集成.
- 开发高效的边缘处理算法对于实现视网形硬件至关重要.
研究的目的:
- 开发一个带有嵌入智能视觉功能的视网形硬件原型.
- 创建一个能够实时感知和响应环境的系统.
- 推进外骨架机器人协助身体残疾人的能力.
主要方法:
- 开发了一个4096像素的矿图像传感器阵列作为核心模块.
- 采用了一种模仿视网膜电路的光电探测器-晶体管几何.
- 实现了具有对比度增强和1D特征提取算法的自适应成像.
主要成果:
- 在低光条件下 (10微瓦/厘米2) 达到~620%的对比度增强.
- 证明了宽带,超高和可重新配置的光响应性.
- 成功地将视觉场景分解成编码的时空信息.
结论:
- 视网形态系统提供了具备适应性成像,现场处理和决策的体现智能.
- 这项技术对自主机器人应用具有重大潜力,特别是在辅助机器人领域.
- 基于矿的传感器阵列为先进的机器人视觉提供了可扩展和有效的解决方案.
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