Compact single-shot metalens depth sensors inspired by eyes of jumping spiders
Compact single-shot metalens depth sensors inspired by eyes of jumping spiders
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DOI：
10.1073/pnas.1912154116
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发表时间：
2019-11-12
影响因子：
11.1
通讯作者：
Zickler, Todd
中科院分区：
文献类型：
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作者：
Guo, Qi;Shi, Zhujun;Zickler, Todd
跳蛛（跳蛛科）依靠精确的深度感知来捕食和导航。尽管它们的大脑很小，但它们通过使用专门的光学装置实现了深度感知。每只主眼都有一个多层视网膜，可以同时接收不同散焦程度的多幅图像，从这些图像中解码距离，计算量相对较少。我们介绍了一种紧凑的深度传感器，灵感来自跳蜘蛛。它结合了超透镜光学，在亚波长尺度上修改入射光的相位，并通过有效的计算来测量图像离焦的深度。该传感器不是使用多层视网膜来传递多个同时的图像，而是使用超透镜来分裂通过光圈的光，并在单个平面光敏器的不同区域同时形成两个不同的散焦图像。我们展示了一个系统，该系统部署了一个直径为3毫米的超透镜，可以在10厘米的距离范围内测量深度，每个输出像素使用不到700次浮点运算。与以往的无源深度传感器相比，我们的超透镜深度传感器结构紧凑，单次拍摄，计算量少。纳米光子学和高效计算的结合使人工深度传感在毫米级、微瓦级平台（如微型机器人和微型传感器网络）上更接近可行。
Jumping spiders (Salticidae) rely on accurate depth perception for predation and navigation. They accomplish depth perception, despite their tiny brains, by using specialized optics. Each principal eye includes a multitiered retina that simultaneously receives multiple images with different amounts of defocus, and from these images, distance is decoded with relatively little computation. We introduce a compact depth sensor that is inspired by the jumping spider. It combines metalens optics, which modifies the phase of incident light at a subwavelength scale, with efficient computations to measure depth from image defocus. Instead of using a multitiered retina to transduce multiple simultaneous images, the sensor uses a metalens to split the light that passes through an aperture and concurrently form 2 differently defocused images at distinct regions of a single planar photosensor. We demonstrate a system that deploys a 3-mm-diameter metalens to measure depth over a 10-cm distance range, using fewer than 700 floating point operations per output pixel. Compared with previous passive depth sensors, our metalens depth sensor is compact, single-shot, and requires a small amount of computation. This integration of nanophotonics and efficient computation brings artificial depth sensing closer to being feasible on millimeter-scale, microwatts platforms such as microrobots and microsensor networks.