The technical breakthrough is a new technique the team calls motion-induced aperture sampling, inspired by two ideas familiar from modern imaging: burst photography (the rapid-fire frame stacking your phone uses for low-light shots) and synthetic aperture radar (the satellite technique that turns motion into resolution). The method turns the natural shake of a handheld device into an asset, stitching together faint signals from light that bounces off nearby walls and floors to reveal what's hidden just out of view.
"The most exciting part of this work to me is that we took a capability that used to require a specialized $50,000 imaging setup and put it into the hands of people in robotics, AR/VR, and beyond," says Somasundaram.
As LiDARs become more common, I think this could lead to entirely new forms of machine vision and spatial perception.
Until now, "seeing around corners" has been the domain of specialized optics labs, requiring bulky equipment, careful calibration, and significant expertise. This work points to a different future — one where the capability is plug-and-play and built on hardware millions of people already own. Potential applications span autonomous vehicles that can sense obstacles around blind corners, AR/VR headsets that can track a user's body even when limbs leave the field of view, robots that can navigate complex or textureless spaces more safely, and entirely new categories of consumer experiences yet to be imagined.