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New Depth Sensors Key to Self-driving Cars

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Self-driving cars have undoubtedly been in the limelight for some time now. Beyond any question, it is going to be the next big thing which will carry the torch of new-age technology. We are accustomed to believe that it will be a decade or two before we see one on the roads. Let me tell you, it is not so!

Researchers of the Camera Culture group at MIT’s Media Lab have seen to it. They have developed new sensors for time-of-flight (ToF) imaging system that provides very high depth resolution of the objects. For an object 2 metres away from the sensors the depth resolution is about 3 micrometres. Basically, ToF is an imaging system that projects light wave in different directions between very short intervals of time. It then records the time taken by the wave that hits the object to travel back and calculates the distance of object from the sensor.

Also, the wave goes through a change in phase after bouncing back from the object. This change in phase determines the orientation of the object through certain algorithms. The sensors developed by the researchers can make self- driving cars practical. They applied the concept of beats that is used in acoustics to the light pulses. For an example, if a ToF system is firing light at an object at a rate of 1,000,000,000 (billion) pulses per second, then the reflected light wave is combined with a light wave pulsing 999,999,999 times a second and the result will be a light wave pulsating once per second which is easy to detect by the light capturing sensors. This is similar to “beat” and provides phase information which is used to collect data. What the researchers did is that they modulated the reflected wave by employing the similar technology that is used to produce the wave. It simply means that the already pulsed light is pulsed again.

This approach can be a game changer for self-driving cars. The major obstacle in the development of self-driving cars is fog as it scatters light and deflects them at odd angles. This problem can be tackled by the new system. The high frequency (Gigahertz) light waves used in the system are found to be more effective than the low frequency ones inherently. Low frequency waves scatter the light and cause a slight shift in phase, which gives inaccurate data, but with high frequency systems the phase shift is quite large. Therefore, when these scattered light signals meet, they actually cancel out each other. This cancellation helps in recognising the true signal easily. With this new innovation, the development of self-driving car will certainly make a leap.

Points: “time of flight”, an approach that gauges distance by measuring the time it takes light projected into a scene to bounce back to a sensor. New approach to time-of-flight imaging that increases its depth resolution 1,000-fold. That’s the type of resolution that could make self-driving cars practical.

The new approach could also enable accurate distance measurements through fog, which has proven to be a major obstacle to the development of self-driving cars. Existing time-of-flight systems have a depth resolution of about a centimeter. As you increase the range, your resolution goes down exponentially. At distances of 2 meters, the MIT researchers’ system, by contrast, has a depth resolution of 3 micrometers. tests suggest that at a range of 500 meters, the MIT system should still achieve a depth resolution of only a centimeter.

If a time-of-flight imaging system is firing light into a scene at the rate of a billion pulses a second, and the returning light is combined with light pulsing 999,999,999 times a second, the result will be a light signal pulsing once a second — a rate easily detectable with a commodity video camera. And that slow “beat” will contain all the phase information necessary to gauge distance. Kadambi and Raskar simply modulate the returning signal, using the same technology that produced it in the first place. That is, they pulse the already pulsed light. The result is the same, but the approach is much more practical for automotive systems.

“The fusion of the optical coherence and electronic coherence is very unique”, Raskar says. “We’re modulating the light at a few gigahertz, so it’s like turning a flashlight on and off millions of times per second. But we’re changing that electronically, not optically. The combination of the two is really where you get the power for this system”.

Gigahertz optical systems are naturally better at compensating for fog than lower-frequency systems. Fog is problematic for time-of-flight systems because it scatters light: It deflects the returning light signals so that they arrive late and at odd angles. Trying to isolate a true signal in all that noise is too computationally challenging to do on the fly.

With low-frequency systems, scattering causes a slight shift in phase, one that simply muddies the signal that reaches the detector. But with high-frequency systems, the phase shift is much larger relative to the frequency of the signal. Scattered light signals arriving over different paths will actually cancel each other out: The troughs of one wave will align with the crests of another. Theoretical analyses performed at the University of Wisconsin and Columbia University suggest that this cancellation will be widespread enough to make identifying a true signal much easier.

“I think it is a significant milestone in development of time-of-flight techniques because it removes the most stringent requirement in mass deployment of cameras and devices that use time-of-flight principles for light, namely, [the need for] a very fast camera,” he adds. “The beauty of Achuta and Ramesh’s work is that by creating beats between lights of two different frequencies, they are able to use ordinary cameras to record time of flight.”

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New Depth Sensors Key to Self-driving Cars. (2019, January 03). GradesFixer. Retrieved July 26, 2021, from
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