New Imaging System to Make Self-Driving Cars Practical
The system uses "time of flight" - an approach that gauge distance by measuring the time it takes light projected into a scene to bounce back to a sensor.
Image for representation only. (Image: Reuters)
MIT scientists have developed a new imaging system that can more quickly and accurately gauge distance, an advance that could make self-driving cars practical. The system uses "time of flight" - an approach that gauge distance by measuring the time it takes light projected into a scene to bounce back to a sensor.
The new approach to time-of-flight imaging developed by researchers at Massachusetts Institute of Technology (MIT) in the US increases its depth resolution 1,000-fold. "As you increase the range, your resolution goes down exponentially. Let's say you have a long-range scenario, and you want your car to detect an object further away so it can make a fast update decision," said Achuta Kadambi, a PhD student at MIT.
"You may have started at one centimeter, but now you are back down to a resolution of a foot or even five feet. And if you make a mistake, it could lead to loss of life," said Kadambi.
At a range of two meters, existing time-of-flight systems have a depth resolution of about a centimetre. That is good enough for the assisted-parking and collision-detection systems on today's cars, according to researchers including Rajiv Gupta and Ramesh Raskar from MIT.
At distances of two metres, the new system, by contrast, has a depth resolution of three micrometers. Kadambi also conducted tests in which he sent a light signal through 500 meters of an optical fibre with regularly spaced filters along its length, to simulate the power falloff incurred over longer distances, before feeding it to his system. The tests suggest that at a range of 500 metres, the MIT system should still achieve a depth resolution of only a centimeter.
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