TetraVue raises $10M to build better sensors for self-driving cars

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Many if not most of the companies currently developing autonomous vehicles buy their object recognition equipment from Mobileye N.V., but it’s hardly the only provider out there.

One of the most promising contenders is a low-key firm called TetraVue Inc. that entered the spotlight for the first time on Thursday after revealing that it has raised $10 million in funding. The investment was led by the venture capital arm of German industrial giant Robert Bosch GmbH and an early-stage fund called Nautilus Venture Partners. The latter firm was founded in 2015 by former executives from Foxconn Technology Group and Samsung Group, which incidentally both contributed to this week’s round.

TetraVue will use the new capital to commercialize its namesake imaging system, which has been in development for nearly a decade. The platform is touted as a major evolution of the Light Detection and Ranging technology that autonomous vehicles employ to visualize their surroundings.

LIDAR systems trace their origins back to 1960s and take a fairly straightforward approach to object detection. The typical implementation combines a set of cameras with laser diodes configured to generate rapid bursts of light that fall outside the visible spectrum. These waves are reflected off the environment back into the cameras to produce a three-dimensional map. For the sake of improving resolution, the laser array is usually installed on a mount that rotates several hundreds times a second sort of like a radar dish so to generate more light signals.

TetraVue claims that its technology eliminates the need for such rotation and thus reduces power consumption while simplifying the overall system design, which in turn lowers the risk of technical problems. Moreover, the platform is capable of picking up the returning pulses using cameras with standard CMOS and CCD semiconductor technologies that are cheaper than the specialized sensory gear often used in LIDAR implementations.

Yet despite all these advantages, the system’s efficiency isn’t even its main selling point. TetraVue claims that its technology has been shown to provide up to 10 times better resolution than alternatives in early testing and can detect objects from more than 650 feet away, which makes it possible to identify potential obstacles faster. The platform can furthermore do so in “any weather condition” during both day and night.

TetraVue sees its technology coming handy not only for autonomous vehicles but also in use cases such as mapping and augmented reality. The startup’s value proposition may just be appealing enough to take on MobileEye, but it still faces an uphill competitive battle. The latter firm boasts deals with many of the world’s top car makers and marked its latest win just today after announcing the completion of a project to outfit 4,500 for-hire vehicles in New York City with its collision avoidance technology.

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