Cognata, Partners Bring Digital Twin-Based Simulation into Microsoft Azure

Autonomous driving technologies developer and computer vision company Cognata will collaborate with Microsoft on its Automated Driving Perception Hub (ADPH) global program. The program, which will run on Microsoft Azure, aims to enable automotive customers to virtually and efficiently evaluate advanced driver assistance systems (ADAS)/autonomous vehicle (AV) sensors through digital twin-based sensor simulation.

Cognata's ADPH allows sensors to be evaluated against a common set of industry-standard scenarios, and their performance to be analyzed quickly and easily. The platform incorporates accurate, manufacturer-approved sensor modeling with a wide spectrum of sensors, such as RGB cameras, with varying lens distortions, point-cloud lidar systems, and infrared thermal cameras all integrated with a deep neural network-based photorealistic layer.

The program technology will additionally incorporate EPYC processors — provided by semiconductor company AMD — and graphics processing units from Radeon.

A visualization of Cognata’s advanced sensor viewer. Courtesy of Cognata.

A visualization of Cognata’s advanced sensor viewer. Courtesy of Cognata.

In a separate announcement, Lidwave, a developer of lidar-on-a-chip sensors, said this week that its MonoStaticOne sensor is available for simulation of industrial and automotive use cases on Cognata's perception hub. The two companies will hold a joint technology demonstration at CES 2024 in Las Vegas next week.

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Published: January 2024

Glossary

lidar: Lidar, short for light detection and ranging, is a remote sensing technology that uses laser light to measure distances and generate precise, three-dimensional information about the shape and characteristics of objects and surfaces. Lidar systems typically consist of a laser scanner, a GPS receiver, and an inertial measurement unit (IMU), all integrated into a single system. Here is how lidar works: Laser emission: A laser emits laser pulses, often in the form of rapid and repetitive laser...
machine vision: Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
computer vision: Computer vision enables computers to interpret and make decisions based on visual data, such as images and videos. It involves the development of algorithms, techniques, and systems that enable machines to gain an understanding of the visual world, similar to how humans perceive and interpret visual information. Key aspects and tasks within computer vision include: Image recognition: Identifying and categorizing objects, scenes, or patterns within images. This involves training algorithms...

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