18 NEWS
AW MAY 2022
Zebra Technologies Acquires Matrox’s Imaging Division By David Miller
Senior Technical Writer
W
ith its ability to help automate quality control, guide flexible pick-and-place systems, and simplify inventory tracking procedures, machine vision is of growing importance to industrial automation technology. By converting light captured via a smart camera into various types of digital image outputs, machine vision sensors provide a wealth of complex data that can allow automated systems to identify objects, navigate complex and changing workspaces, and analyze materials in a manner that was previously out of reach. To expand its own machine vision offerings, Zebra Technologies—a company focused on data capture and automatic identification products—has acquired the imaging division of electronic company Matrox. Matrox, which also produces audio-video software and hardware for the broadcast market will retain this division.
Shortly before the acquisition, Zebra established a machine vision business unit with the intention of devoting more resources to its machine vision products. "Through the introduction of more advanced, image-based sensing technologies and softwarebased visual analytics, Zebra can give customers greater visibility into the status of assets at the operational edge of their businesses to…operate more efficiently with increasingly automated, data-powered workflows, " said Donato Montanari, vice president and general manager of machine vision for Zebra. Until the acquisition is finalized later this year, Montanari said Zebra will focus on tapping the expertise of Matrox’s machine vision engineers to improve future product releases rather than on rebranding Matrox technologies. More specifically, enhancements to Zebra’s automatic identification and data capture technologies, barcode and RFIDbased data capture devices, and indoor location tracking offerings will be achieved by adding more advanced machine vision hardware, software, and
services, such as 3D sensing and frame grabbers. Zebra’s acquisition of Matrox’s imaging division follows its 2021 acquisition of machine vision software provider Adaptive Vision. That acquisition provided Zebra with access to enhanced machine learning and deep learning capabilities, improving the analytics capabilities of the company’s machine vision software. "Zebra’s enterprise asset intelligence vision is for every asset and front-line worker on the edge to be visible, connected, and fully optimized," Montanari said. "Matrox Imaging will position Zebra to provide customers a broader spectrum of information about their assets, above and beyond identification. They will further our ability to enrich complex workflows with greater visibility, enabling the automation of repetitive tasks and answering a wider range of questions related to the inspection of assets such as build quality, consistency, proper quantities, and more."
Improving Automation’s Energy Efficiency with Neuromorphic Sensor Technology By David Miller
Senior Technical Writer
W
hile the term industrial automation typically refers to machines with the ability to perform highly structured, pre-programmed tasks in place of human labor, the term industrial autonomy describes systems that are capable of adapting independently to diverse circumstances with minimal human intervention. For instance, an autonomous robot might be capable of learning to grip an unfamiliar object or navigate a new space without assistance from a human programmer. Artificial intelligence and machine learning provide the internal processing power necessary to enable this, but powerful external sensors are also needed to help robots and other automated technologies perceive and respond to their environments. That’s why technologies such as “sensor fusion,” which grants a single sensor the ability to monitor multiple input types, are on the rise. These advanced
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sensor technologies are made possible by the exponential growth in computing capacity over the past several decades, which allowed more intelligence to be packed into smaller and smaller devices. However, the added processing power comes at a cost— namely, an increase in energy consumption. To overcome this challenge, FraunhoferGesellshaft, a major European applied research organization, has launched NeurOSmart, a joint research initiative with the Fraunhofer Institute for Photonic Microsystems. The project aims to use neuromorphic electronics, which are modeled on the operations of the human brain, to use less energy. As part of this project, neuromorphic sensors will be installed in robotic systems for use in manufacturing environments with the goal of increasing their energy efficiency. The data processing performed by neuromorphic sensors is “realized by a novel analog computer memory technology that is also capable of performing computational operations when data is newly acquired in the system,” explained Michael Mensing, a scientist and project leader at the
Fraunhofer Institute for Photonic Microsystems. “In practice, this is used to recognize objects and their behavior accurately and in real time. Until now, this mode of operation has required several separately developed components in computers and particularly energy-intensive communication between them.” According to the Fraunhofer Institute for Photonic Microsystems, this new approach makes use of integrated electronics that allow for the parallel development of models for object recognition and classification that are specially adapted to individual sensors. This allows for a faster response time, increased data protection, and significant energy savings compared to current methods. The NeurOSmart Initative has a project budget of 8 million Euros and will operate for four years, during which it will attempt to integrate its neuromorphic sensor electronics with a complex light detection and ranging (LiDAR) system.
4/28/22 9:05 AM
