A new software system developed at the University of Michigan uses video game technology to help solve one of the most daunting hurdles facing self-driving and automated cars: the high cost of the laser scanners they use to determine their location.
Ryan Wolcott, a U-M doctoral candidate in computer science and engineering, estimates that the new concept could shave thousands of dollars from the cost of these vehicles. The technology enables them to navigate using a single video camera, delivering the same level of accuracy as laser scanners at a fraction of the cost.
"The laser scanners used by most self-driving cars in development today cost tens of thousands of dollars, and I thought there must be a cheaper sensor that could do the same job," he said. "Cameras only cost a few dollars each and they're already in a lot of cars. So they were an obvious choice."
Wolcott's system builds on the navigation systems used in other self-driving cars that are currently in development, including Google's vehicle. The navigation systems use three-dimensional laser scanning technology to create a real-time map of their environment, then compare that real-time map to a pre-drawn map stored in the system. By making thousands of comparisons per second, they are able to determine the vehicle's location within a few centimeters.
The software converts the map data into a three-dimensional picture much like a video game. The car's navigation system can then compare these synthetic pictures with the real-world pictures streaming in from a conventional video camera.
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