(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
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,
At Civil Maps, we’ve developed technology that allows analog and autonomous test vehicles to navigate roads using crowdsourced, HD, 3D maps rather than current, high-latency and high-compute methods. We are excited to share with you one key part of this solution, designed for those working on self-driving cars. 2016 was a pivotal year for our
This weekend, we’ll be heading over to Thunderhill Raceway in Willows, CA for the Self- Racing Cars event, with the goal of ultimately providing cognition and 3D mapping for autonomous competition vehicles. The two-day race was launched just last year and is gaining an enthusiastic following from local autonomous vehicle technology companies. Bringing together a
A few weeks ago, Civil Maps hosted our very first webinar from the conference room of our shiny new offices in downtown San Francisco. It was the first part of a series we’re presenting called Getting Started with Sensors. We talked about LiDAR, one of the sensor types we use for creating 3D semantic map
