Ambarella and Momenta unveil a collaborative HD mapping platform for autonomous vehicles. The combined concoction leverages Ambarella’s CV22AQ CVflow computer vision system-on-chip (SoC) and Momenta’s deep learning algorithms to provide HD map solutions, including mapping, localization for autonomous vehicles, and map updates through crowdsourcing.
Momenta’s vision-based HD semantic mapping solution is highly scalable and production-ready. Through crowdsourcing, the solution can create a closed feedback loop of big data, AI, and HD map updates. Based on localization, Momenta discovers changes in the map elements and provides frequent updates to the cloud.
The CV22AQ is manufactured in an advanced 10-nanometer process, providing the ultra-low power consumption required for the design of compact automotive systems. Its CVflow architecture delivers real-time processing with up to 8-Mpixel resolution video at 30 fps for high-precision deep learning based object recognition. Its image signal processor delivers clear image quality in low-light environments, while high dynamic range (HDR) processing extracts more image detail in high-contrast scenes.
Using CV22AQ, Momenta can use a single monocular camera input to generate two separate video outputs, one for vision sensing (perception of lanes, traffic signs, and other objects), and another for feature point extraction for self-localization and mapping (SLAM) and optical flow algorithms. Ambarella provides a complete set of tools to help users port neural networks to the CV22AQ SoC. Based on the tool chain, Momenta can quickly migrate deep learning perception models to embedded platforms and achieve an accurate output. For more details, visit Ambarella and Momenta.