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Photonics

Spider eyes inspire compact camera

Metasurface lens could be used in low-power, compact depth sensors for robots and cell phones

by Katherine Bourzac
October 31, 2019 | APPEARED IN VOLUME 97, ISSUE 43

 

09743-scicon8-spider.jpg
Credit: Shutterstock
Jumping spiders' simple eyes are capable of sophisticated depth perception.

Jumping spiders are brilliant hunters, accurately leaping relatively large distances to surprise their prey. They can plan these surprise pounces just right thanks to their fantastic depth perception. Each of their two principal eyes has a double-layered retina. Spider behaviorists believe the creatures use their poppy-seed-sized brains to compare the relative sharpness of the two images from the two retinal layers and use that information to estimate distances.

“We’re still not 100% sure how spiders actually achieve this because we don’t read spider minds,” says Zhujun Shi, a grad student in physics at Harvard University. Still, she and collaborators Qi Guo and Federico Capasso were inspired by the critters and decided to mimic their retinas to make a simple depth-sensing camera that could lead to simple, low-power sensors for cell phones and robots (Proc. Natl. Acad. Sci. U.S.A. 2019, DOI: 10.1073/pnas.1912154116).

09743-scicon8-flies.jpg
Credit: Qi Guo and Zhujun Shi
The two lenses of a spider-inspired metasurface have different focal lengths and focus on different parts of this scene of two flies (left). A spider-inspired imaging system compares the relative sharpness of the two images (center and right) to estimate the distance of the flies.

Existing systems require an infrared light source or moving parts or both. The team made the retinas from a metasurface, a material with a designed structure that interacts with light in specific ways. In particular, the device is made up of two regions of patterned titanium dioxide nanopillars, each of which has a different focal length, to mimic the double-layered spider retina. They researchers combined the 3 mm diameter metalens with an optical sensor and fed the collected data through an adapted image-processing algorithm to determine the depth of imaged objects.

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