Engineering Updates

Company Updates, Engineering Updates

Partnership with Civil Maps and Renovo: Building a Universal Operating System for Automated Mobility


By Paul Drysch, VP of Sales and Business Development Today’s autonomous vehicle and automated mobility market looks a lot like the early days of the personal computer industry: many players, each building its own proprietary machine: a highly automated vehicle (HAV). When a universal, hardware-agnostic computer operating system (OS) finally came along, it allowed specialized

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Company Updates, Engineering Updates

When Augmented Reality Does Its Job, We’ll All Want a Self-Driving Car


 By Sravan Puttagunta, CEO and Co-founder, Civil Maps We’ve all seen augmented reality (AR) in shows such as Monday Night Football, in which broadcasters superimpose virtual lines and diagrams on the field, manually marking up video playbacks to highlight key maneuvers and strategies. This helps viewers easily focus on points of interest, rather than looking

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Engineering Updates, Updates

Moving to Arm®: A Marriage of Minimums


By Sravan Puttagunta, CEO and Co-founder of Civil Maps Civil Maps is excited to announce that we’ve migrated our edge-based HD mapping and localization solution to the Arm® family of processors. Arm is the licensor to the largest ecosystem of automotive grade system-on-chips (SoC) and system-on-modules (SoM), with its chips already found in 85% of

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Engineering Updates

Introducing: The Fingerprint Base Map™ for Autonomous Vehicle Mapping and Localization


By Scott Harvey, Engineering Today, as CES 2018 kicks off, Civil Maps officially announces something we’ve been working on and refining for quite a while: our Fingerprint Base Map™ technology. It is a critical component of the breakthrough system that we’ve developed to enable cognition for self-driving cars. The Fingerprint Base Map is a key

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Engineering Updates

Edge Mapping: Our Journey from Trains to Self-Driving Cars


By Sravan Puttagunta, Co-founder & CEO of Civil Maps The story of Civil Maps did not begin with cutting-edge self-driving cars, but with old-fashioned trains. The story is worth sharing, as it helps explain our unique approach to solving many of the toughest mapping and localization challenges facing the autonomous driving industry today. Specifically, our

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Engineering Updates

Fusing GPS + IMU For Fun and SBETS


(Getting Started with Sensor Data Webinar Series, Sensor Fusion –  Part 1) By David Bulnes and Jian Wu, Engineering Last month, we held the second webinar in our ongoing and live-broadcasted Getting Started with Sensor Data series. (We’ve also published an archive of the video playlist here.) In that session, we covered the basics about

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Engineering Updates

Cognition for Autonomous Cars Using 6D Localization


To drive autonomously, vehicles need software which emulates the routines of natural human cognition (processes used to judge, plan, acquire knowledge, or otherwise — “think”). Autonomous vehicles must be able to understand the world that surrounds them, and this environmental context can be provided in the form of a machine-readable, high-definition “semantic map.” Detailed 3D semantic maps,

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