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

Nodar, a maker of software for 3D-vision cameras in autonomous vehicles, announced today that it has landed $12 million in series A funding, led by global venture capital firm New Enterprise Associates (NEA) with participation from existing investor Rhapsody Venture Partners. 

The funds will be used for research and development for Nodar’s core technology, as well as expanded sales and marketing initiatives, the Somerville, Massachusetts-based company said.

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

Nodar’s target market of SAE L2+ and L3 (SAE indicates various levels of driving automation) passenger-vehicle advanced driver assistance systems (ADAS) and L4 trucks is projected to reach 250 million vehicles between 2025 and 2030, Jiang said.

Nodar aims for disruption

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

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

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

Nodar’s Hammerhead uses off-the-shelf automotive-grade cameras and standard compute platforms to deliver ultra-long-range sensing — beyond 1,000 meters — with precision. With cameras mounted on the roof of a passenger vehicle, Nodar Hammerhead has demonstrated the ability to detect a 10 centimeter brick at 150 meters, Jiang said. Being able to detect very small objects at long range is an indispensable requirement for any self-driving vehicle operating safely at highway speeds because of the time and distance needed to stop or avoid the object, Jiang said.

“Every AV needs super-reliable 3D information to understand its surroundings and make safe decisions,” Greg Papadopoulos, venture partner at NEA, said 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 a solution was possible. “Nodar Hammerhead is the result of this work and has the potential to become a ubiquitous component in every driver-assisted and self-driving vehicle in the world,” Jiang said.