MIT scientists will teach unmanned vehicles to navigate in heavy fog

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2018-03-23 13:30:06

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MIT scientists will teach unmanned vehicles to navigate in heavy fog

Ensuring the safe movement of self-driving cars very — a new direction for their launch. Especially in light of the recent . The greatest danger any vehicle is in low light conditions and visibility, particularly in the fog. And recently researchers from mit have developed a method that allows lidars (basic elements of orientation in space) great to "see" the fog.

Essentially any lidar is a device that emits a laser beam and based on its reflection receives information about the surrounding objects. With a huge amount of advantages of lidar has a significant drawback: clean air does not interfere with his work, but to see anything through the dense fog device is not capable of. A group of scientists under the leadership of Ramesh raskar of the invented method that enables the lidar to receive a signal reflected from objects even in very dense fog.

Distribution of photons depending on the density of fog

This Happens as follows: the laser emits pulses in the area of the fog, and next to the receiving device in a special chamber, consisting of single-photon detectors. They record the return time of each photon. Every recorded "frame" contains information on the time of receipt of a photon. Then a computer program constructs the diagram in which each column describes the number of registered photons and builds on the basis of this data about the region of object location.

Receive signal from fog and from the objects located in it

During a series of experiments, the scientists tested their method in artificially created fog. It turned out that in a time when direct visibility is 37 inches, the modified lidar detects objects at a distance of 57 cm. At the moment, the experiments continue and authors will continue to improve the technology. In particular, the main problem now is that lidar can capture only static objects.

Http://www.youtube.com/watch?v=CkR1UowJF0w

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