Multi-camera 3D-vision provider Nodar secures funding to drive automation

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Nodar, maker of software for 3D-vision cameras in autonomous vehicles, announced today that it has invested શ્રેણી 12 million in a Category A fund, led by global venture capital firm New Enterprise Associates (NEA), in partnership with current investor Rhapsody Venture Partners.

Funds will be used for research and development for Nodar’s core technology, as well as for an extended sales and marketing initiative, Somerville, Massachusetts-based. The company said.

Nodar’s long-range, high-resolution, real-time camera-based software is an important security component in the development of driver-assisted and fully autonomous vehicles, CEO Leif Jiang said in a media advisory.

The target market for SAE L2 + and L3 (SAE) SAE L2 + and L3 (SAE indicates) passenger-vehicle advanced driver assistance systems (ADAS) and L4 trucks is estimated to reach 250 million vehicles between 2025 and 2030, Jiang said.

As an alternative to LiDAR (a detection system that works on the principle of radar but uses laser light) in the L2 + and L3 automotive applications, and as the L4 sensor dominant 3D sensor in fusion environments, Nodar has the ability to intercept fundamentally. Industry, Jiang said.

Nodar’s flagship product, Hammerhead, uses advances in processing, computer vision algorithms and camera technology to create ultra-precise 3D-point clouds from two or more cameras, Jiang said. Nodar’s patented algorithms maintain the alignment between the cameras mounted independently on the vehicle, giving OEM flexibility on where to place the cameras.

This auto-calibration capability not only ensures reliable depth measurements despite road and vehicle vibrations, but also enables the camera to be mounted remotely, which improves the range and accuracy of the vision system through wide-baseline triangles, Jiang said.

Nodar’s hammerhead uses off-the-shelf automotive-grade cameras and standard compute platforms to deliver ultra-long-range sensing – over 1,000 meters – with precision. With a camera mounted on the roof of the passenger vehicle, the noder hammerhead demonstrated the ability to detect 10-cm bricks at 150 meters, Jiang said. Jiang said it is imperative for any self-driving vehicle to be able to detect very small objects over a long range safely because of the time and distance required to stop or avoid the object.

“Every AV needs super-reliable 3D information to understand its surroundings and make safe decisions,” said Greg Papadopoulos, venture partner at NEA, in a media advisory.

Jiang said he spent 13 years developing optical ranging systems, and seeing advances in computing, algorithms and camera technology, he said he knew the solution was possible. “Noder Hammerhead is the result of this work and has the potential to be a ubiquitous component in every driver-assisted and self-driving vehicle in the world,” Jiang said.

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