Integrated Automation Replaces Single-Technology Systems
Shikany described a growing trend toward integrated automation solutions, noting that today’s projects often combine multiple technologies into single systems.
“Back in the day, it was, ‘I may need just a robot,’ or ‘I may need just a vision system’... but at a show like Automate...you get to see in one hardware package with a humanoid robot vision systems, sensing, articulation, robotics, mobility in one package,” Shikany said. This convergence reflects the reality that automation no longer happens in isolated technology silos.
AI Elevates Vision Performance
In the machine vision domain, systems have evolved beyond simple pass/fail inspection to more intelligent, adaptive applications. “Traditional machine vision is going more from simple pass-fail inspection applications to a more flexible, dynamic, adaptive, intelligent understanding environments,” Shikany explained.
He said that AI and deep learning expand vision capabilities substantially but stressed they must work within the context of overall system design. “It needs to come together in the whole picture with good system design, the proper hardware that it’s using, the lighting conditions, all of that.”
Speaking on AI specifically, he said that vision systems have made advances in classification, segmentation, and defect detection. “AI vision can do so much more in terms of classification and detection and different types of segmentation and defect detection... It can do those things better now than it could in previous years, and...at greater speed and with more accuracy.”
However, he cautioned, “It’s not one-size-fits-all,” and encouraged engineers to combine AI exploration with foundational vision principles.
