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Aurora Autonomy/Engineering

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The technological foundation accelerating development of the Aurora Driver

By the Aurora Team|October 14, 2021|7 min read

FMCW lidar: The self-driving game-changer

By the Aurora Team|April 9, 2020|7 min read

Online to offline: Turning real-world experience into virtual tests

By the Aurora Team|May 12, 2020|9 min read

Forecasting: Understanding interaction

By Drew Bagnell|November 10, 2021|7 min read

Latest

Continuous real-time sensor recalibration: A long-range perception game-changer

Our automatic, real-time miscalibration detection and recalibration capability helps ensure that the Aurora Driver’s perception system is...

By the Long-Range Perception Team
March 15, 2023|4 min. read

Introducing Au: Our open source C++ units library

For years now, our units library has been making it easy to handle units safely, and develop our code more quickly. Now, at last, we're sharing it...

By Chip Hogg
February 08, 2023|5 min. read

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Aurora’s Data Engine: How we accelerate machine learning model workflows

Everything from perception to motion planning is powered in part by the datasets and models developed in a cycle commonly referred to as the “Data...

By Ankit Aggarwal and Vinay Anantharaman
January 17, 2023|7 min. read

Lightbox: Autonomy visualization at Aurora

Lightbox is a completely web-based application that allows users to quickly customize their viewing experience and dig deep into the parts of the...

By the Lightbox team
September 15, 2022|5 min. read

A piece of the perception puzzle: Harnessing the range view

At Aurora, we are continuously innovating in lidar sensor development, allowing our autonomous vehicles to see lidar points from farther away,...

By Shivam Gautam
August 31, 2022|5 min. read

Batch API part 3: Supercomputing at scale

As Aurora continues to grow and prepare for the launch of Aurora Horizon and Aurora Connect—our autonomous trucking and ride-hailing...

By the Compute Infrastructure team
April 04, 2022|8 min. read

TetrysTables: Speeding up machine learning model development with shared datasets

Autonomous vehicles understand the world by processing enormous amounts of data acquired via sensors.

By Yevgeni Litvin
March 14, 2022|8 min. read

Batch API part 2: Resource management

Computing power is an extremely valuable resource that can determine a technology’s ability to scale. We believe self-driving technology will someday...

By the Compute Infrastructure team
January 25, 2022|11 min. read

Batch API part 1: Aurora’s supercomputer

Self-driving is full of technical challenges, and as a company focused on delivering the benefits of self-driving technology safely, quickly, and...

By the Compute Infrastructure team
December 09, 2021|11 min. read

Perception at Aurora: No measurement left behind

How we’re blending state-of-the-art machine learning and engineering in our perception system to help the Aurora Driver handle the unexpected.

By the Aurora Team
November 14, 2021|4 min. read

Forecasting: Understanding interaction

One of the greatest challenges in self-driving is the interaction with other actors on the road—whether drivers, cyclists, or pedestrians. AVs would...

By Drew Bagnell
November 10, 2021|5 min. read

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