Random bin picking is a challenge for vision-guided robotics (VGRs), but manufacturers are developing software and end-of-arm-tooling (EOAT) technology to make the process more efficient.
Machine vision and artificial intelligence (AI) are making their way into production and manufacturing and improving inspection practices by making it automated.
Picking the right machine vision lens requires the user to consider the type of lens, sensor, and more.
Digitalization and new manufacturing techniques have paved the way for a dramatic improvement in lead times.
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Advanced driver assistance systems (ADAS) offer simplification of the driving process, including reduction of driver distraction and inattention and embedded vision is integral to these advances.
Northwestern Engineering researchers have developed a chip-based terahertz frequency comb that works at room temperature and is designed for medical and biological screening.
Deep embedded vision systems can work without operating systems and feature advanced algorithms for processing raw image streams from integrated image sensors.
2-D and 3-D automated optical inspection (AOI) scan printed circuit boards (PCBs) for both catastrophic failure and quality defects, but each inspection system has particular strengths and weaknesses.
The AIA reported that machine vision component and system sales declined 4.5% in the first quarter of 2019 compared to the same period in 2018.