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Laser Tech for Autonomous Cars Reveals Objects Hidden Around Corners

Someday self-driving cars could react to hazards before passengers even see them - thanks to a laser-based imaging technology being developed at Stanford University  that can see around corners. Tech Briefs spoke to the researchers about the new technology, and the future of autonomous driving.

Topics:
Automation Automotive Imaging Photonics Robotics Sensors Transportation

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    Transcript

    00:00:00 [MUSIC PLAYING] Stanford University. The idea is that we want to image objects where we don't have direct line of sight. That is, we want to capture an image of an object where there's an occluder-- something blocking the direct view of that object. The technique works very similar to LIDAR systems

    00:00:25 and autonomous driving. You have a laser that shoots a very short pulse of light into the scene. Some of the light is directly reflected. What we're looking for are indirect reflections where you shoot a short laser pulse into the scene, the light scatters outside the line of sight of the camera-- We're interested in this multiply scattered light. So as light reflects off the wall, interacts with this unknown object,

    00:00:49 and then comes back to our sensor, we are actually picking up information about the geometry of this object that we can't directly observe. These are, at most, a few photons that we're recording, and they don't really resemble the shape of the scene that we're trying to recover-- this hidden scene. So we need to build computational reconstruction methods to try to resolve these shapes that we're looking for.

    00:01:09 We found a way to actually do this, a very memory-efficient, computationally-efficient way that drastically lowers the same amount of resources that's required to actually perform this type of computation. So we go from basically hours to seconds. The applications of no-line-of-sight imaging in general are, of course, in autonomous driving. If your car could look around the corner, it could make decisions probably more reliably, and further ahead of time.

    00:01:36 A benefit of our algorithm, as well, is that it's compatible with existing scanning LIDAR systems, so you can conceivably take our algorithm, apply it to these existing systems, and be able to perform this non-line-of-sight imaging. We're also thinking about, for example, rescue scenarios. You can think about microscopy, where you can look at round structures that are very small, or aerial vehicles that could look through foliage or into buildings.

    00:02:03 So there's a lot of different applications where you want to be able to look outside the line of sight. For more, please visit us at Stanford.edu.