At September’s Autosens in Brussels (an expo and conference focusing on automotive sensor and perception technology), a new “3D Semantic Camera” was launched that could fundamentally change the perception and comprehension of autonomous driving systems. The camera uses hyperspectral analysis and SLAM technology in a single device to identify surrounding objects and analyze road conditions.
From an article by Carla Lauter in SPAR 3D newsletter.
For autonomous vehicle sensing and perception, “seeing” is not the same as understanding. An object detected by sensors could be a statue, a person, a tree, or another car. Most autonomous vehicle perception systems rely on measurements of size, positioning, and velocity to help give clues to an object’s identity. Some solutions leverage machine learning to some degree, but there are limitations as to what you can teach a system to do, especially when it is trying to make correct decisions in an ever-changing, busy environment like a public roadway.
The makers of the 3D semantic camera, Outsight, is a new entity formed from former Velodyne partner Dibotics, who made their name in smart machine perception and real-time processing solutions for 3D data.
One of the primary concerns in autonomous vehicles, especially those aimed for consumer use, is safety – for both the driver and passengers within a car as well as the pedestrians outside of it. For CEO and co-founder of Outsight Cedric Hutchings, it is this safety concern that has driven the development of their products.
“In the US alone, approximately 4 million people are seriously injured by car accidents every year. At Outsight, we believe in building safer mobility by making vehicles much smarter.”
For the full article click here.
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