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Cognex Corp. - Smart Sensor 3-24 GIF LB

3D Sensing for Fast-Moving Robotics

Jul 20, 2022
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About This Webinar
Advancements in machine vision are among key factors that shape automation trends in logistics — for example, the new machine vision capability to capture fast-moving objects in high quality. This task was not possible until recently, as it was only possible to get either fast scanning speed or high-quality 3D data — meaning that for a robot to precisely recognize and handle moving objects, it needed to stop moving for each scan acquisition. This has changed with a novel 3D-sensing approach that enables the capture of dynamic scenes in high resolution and accuracy, without motion artifacts. Allowing robots to handle fast-moving objects without interruption shakes up logistics automation by enabling new tasks, such as the recognition, picking, and sorting of objects moving on a conveyor belt or on an overhead conveyor; palletization and depalletization; the dimensioning of objects, their volume measurement, bounding box estimation, or counting; and an infinite number of other applications — all while in motion.

***This presentation premiered during the 2022 Vision Spectra Conference. For more information on Photonics Media conferences, visit events.photonics.com.

About the presenter:
Svorad StolcSvorad Stolc, Ph.D., is the CTO of the Sensors division at Photoneo. He is an expert in machine vision, artificial intelligence, and parallel computing. In 2001, he received his master's degree from the Comenius University in Bratislava in the Faculty of Mathematics, Physics and Informatics. Afterward, he obtained his doctorate from the Slovak Academy of Sciences in Bratislava and the Technical University of Košice. He worked for the AIT Austrian Institute of Technology in Vienna for several years. During that time, he published several internationally acclaimed scientific articles. At Photoneo, Svorad is responsible for the research and development of the company’s 3D sensing technology.
Sensors & DetectorsautomationroboticsVision Spectravision-guided robotics
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