Winn Hardin is contributing editor for AIA.
Deep learning offers machine vision designers a powerful new tool for advanced inspection and it's getting easier to apply thanks to technology advances.
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 enables a whole new perspective on what humans can inspect, analyze, sort, and read and technologies such as infrared, multispectral, and time of flight are changing the landscape.
System integrators across the industry are fielding more requests to develop complete and detailed systems, which require them to stay ahead of a fast-moving curve.
Advances in 3-D imaging have allowed machine vision users to overcome some challenging inspection tasks and tackles applications 2-D imaging cannot.
Sensor selection is dependent on the application and so is the lighting, which makes optics just as important. However, optics suppliers do struggle to keep pace with the machine vision industry's rapid evolution.
Industry trends impacting the machine vision industry include embedded vision growth, deep learning technology, and global economic uncertainty.
There is growing demand for optimized medical instruments that can provide a solution regardless of location or user expertise and machine vision is crucial in making those advances happen.
Vision-based track-and-trace systems represent big profit potential for companies looking to improve operations and overall safety in industries such as food and beverage, which are subject to potential recalls.
Companies are using software to help realize many machine vision software developments such as ultra-high-dynamic-range imaging and self-analyzing algorithms.