LAS VEGAS & SAN FRANCISCO- CES 2018, LVCC North Hall, Booth #9317 – Civil Maps, the leading developer of cognition software for autonomous vehicles, today announced the availability of Fingerprint Base Map™, the industry’s most robust, scalable solution for precise autonomous vehicle localization and navigation. Architected from the ground up to meet the demands of production scale vehicle autonomy, Fingerprint Base Map™ allows self-driving cars to precisely determine their location in six degrees of freedom (6DoF), while evaluating the safest route to travel. This technology serves as the localization layer in the company’s HD Semantic Map. A video showcasing how it works is available here: https://youtu.be/JOLzVoYq7cE
For self-driving automakers and mobility companies, Fingerprint Base Map™ leverages Civil Maps’ proprietary fingerprinting process to tackle some of the most significant obstacles related to operating autonomous driving programs at scale. Using the company’s novel algorithms, raw point cloud data collected from self-driving cars is transformed into lightweight voxel-based fingerprints, which vehicles use to find their location within a map. Unlike conventional solutions that are dependent on costly processing hardware, large storage arrays, and third-party data centers, Civil Maps’ Fingerprint Base Map™ is created and utilized entirely on-the-edge, in-vehicle.
“With Fingerprint Base Map™, developers now have a reliable, scalable solution for self-driving localization and navigation that does not blow through AV operation budgets,” said Sravan Puttagunta, CEO and Co-founder of Civil Maps. “With our compact map data format, what once required weeks and months to compile, can now be executed more efficiently, in-vehicle, in real-time, and while the car is driving.”
With a data footprint that is up to 10,000 times smaller than traditional base maps, Fingerprint Base Map™ enables autonomous vehicle developers to radically reduce the costs associated with data processing, computing power, data storage, bandwidth, and energy consumption. For example, a conventional base map of San Francisco requires as much as 4 TB of in-car storage, while a voxel-based Fingerprint Base Map™ of the same area comprises only 400 MB. Purpose-built for portability, fingerprinted data can easily be transmitted over existing 3G and 4G cellular network infrastructure, enabling Edge Mapping™, Civil Maps’ process for map creation, map usage, and crowdsourcing.
Highlights of Fingerprint Base Map™
Civil Maps at CES
Civil Maps is showing its autonomous vehicle mapping solutions during CES at booth #9317 in the North Hall of the LVCC. For those interested in a meeting at the conference, please contact: CESinfo@civilmaps.com
About Civil Maps
Civil Maps develops the world’s most scalable, sensor-agnostic platform to provide vehicular cognition for self-driving cars, emulating the mental routines of human cognition used in the tasks of driving, localization, and navigation. With our sensor fusion, fingerprint localization in 6D, and Edge Mapping™ technologies, we help automotive OEMs, mapping providers, and mobility companies accelerate their autonomous driving initiatives in a manner that is significantly more cost-effective and efficient than conventional solutions. From our headquarters in San Francisco and offices in Asia, we work with the most innovative carmakers and partners around the world to bring fully self-driving vehicles to market. Founded in 2015, we have received funding from Ford Motor Company, SAIC, Motus Ventures, the Stanford-StartX Fund, and many other distinguished investors. To learn more about Civil Maps, visit www.civilmaps.com.