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Ambarella Launches Collaborations in Software, Advanced Sensing

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Ambarella Inc., an edge AI semiconductor and software company, and Helm.ai, a developer of next-generation AI software, have released a perception software for the Ambarella CVflow AI SoC architecture to enable Helm.ai’s ADAS system software on the Ambarella platform. The development allows the companies to iterate on technical approaches to the developing needs of the automotive industry.

Helm.ai and Ambarella demonstrated the initial integration of Helm.ai technology at CES 2020. At this year’s event, the companies demonstrated an integration of the Helm.ai full 360° surround-view camera perception stack for L2+/L3 and autonomous driving on Ambarella’s automotive grade CV2FS SoCs. This integration leverages all hardware capabilities of the Ambarella CVflow architecture to optimize the performance of Helm.ai’s AI algorithms while meeting the accuracy goals expected from an automotive-grade solution.
A new perception software for the Ambarella CVflow AI SoC architecture enables Helm.ai’s ADAS system software on the Ambarella platform. Courtesy of Ambarella.
A new perception software for the Ambarella CVflow AI SoC architecture enables Helm.ai’s ADAS system software on the Ambarella platform. Courtesy of Ambarella.

Helm.ai plans to port their software to the latest CV3 domain controller SoC family as part of the ongoing collaboration.

“In the next stage of this collaboration, we are using Ambarella’s scalable CVflow platform to port Helm.ai’s advanced ADAS software onto our new CV3 SoC for single-chip perception of multiple sensors,” said Ambarella President and CEO Fermi Wang. “This central domain controller SoC family can simultaneously process HD radar and vision captures, while providing fusion and path planning for ADAS to L4 autonomous vehicles.”

Joint reference design targets smart building applications

 In a separate collaboration, Ambarella and Lumentum have introduced a joint reference design aimed at smart building applications. The design, called Vision-D, combines Lumentum’s flood illuminator model for time-of-flight 3D sensing with Ambarella’s CV22 edge AI SoC. This combination allows small AIoT sensors with local processing to be blanketed across buildings, supporting occupancy monitoring, intelligent space management, and smart retail.

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According to MarketsandMarkets, the occupancy sensor market is projected to grow from $1.9 billion in 2020 to $3.6 billion by 2025, at a CAGR of 13.3% during the forecast period. The majority of these systems are based on passive infrared sensors that provide only basic information about occupants and the building environment, while a small number are using cameras that capture identifiable features.

Lumentum and Ambarella said the joint reference design will offer privacy and avoid the high cost of cloud computing. Integrating intelligence directly onto these sensing nodes allows functionality and scalability, such as the creation of digital twins for automated real-time space utilization or hot desking in shared workspaces, they said. Other applications include traffic-based hospitality staffing, cleaning and maintenance alerts, and maximized energy efficiency through HVAC and lighting systems.

“There are currently two choices for occupancy sensing in building automation systems — basic motion-detection devices that preserve privacy, or intelligent camera-based systems that compromise privacy,” said Jerome Gigot, senior director of marketing at Ambarella. “This joint reference design combines Lumentum’s high-performance flood illuminator module with our CVflow edge AI SoC to provide a novel solution for digital transformation that protects occupant privacy.” 

The Vision-D joint reference design is available now. In May 2021, Ambarella and Lumentum, with ON Semiconductor, announced a collaboration on AI processing-based 3D sensing for next-generation AIoT devices. The trio also partnered on access control and smart video security solutions in 2020.



Published: April 2022
Glossary
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...
system on chip
Abbreviated SoC. A single chip containing all the electronic circuits required for a complete, working product. SoCs are similar to microcontroller technology but provide additional components. A SoC for a smartphone can include graphics, audio, video and camera processing in addition to all the microcontroller circuit. By compacting more electronic circuits onto one chip, miniaturizing and creating power efficient technology becomes feasible.
camera
A light-tight box that receives light from an object or scene and focuses it to form an image on a light-sensitive material or a detector. The camera generally contains a lens of variable aperture and a shutter of variable speed to precisely control the exposure. In an electronic imaging system, the camera does not use chemical means to store the image, but takes advantage of the sensitivity of various detectors to different bands of the electromagnetic spectrum. These sensors are transducers...
time of flight
(TOF) The length of time needed for a signal to arrive at and be reflected from the target. The basis of an active autoranging/autofocus system.
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