As we move into 2017, the mobile market will pass the torch of driving CMOS image sensor demand to new high-volume applications. Industries including automotive, healthcare, and even virtual reality are transforming the CMOS sensor market by dictating imaging development.
Among the most common tasks in the industrial environment is picking objects. Objects often must be picked and placed to move them from one stage of industrial processing to another. Robots have proven effective in pick and place environments where all objects are of a similar size and their orientation can be reliably predicted. As vision-guided robotics continues to mature, however, engineers explore new applications.
For most of the modern era, 2D imaging has been used in the lion’s share of inspections. Although the benefits of 3D imaging were well understood in theory, technology took some time to emerge. Even once 3D capabilities became available, they were not always cost-effective. Enter the modern 3D smart sensor.
Vision-guided robotics (VGR) are an exciting synthesis of machine vision and automation technology. A vision-guided robot can respond to its environment using the input from machine vision software. This makes it capable of reacting to changes around it better than a robot that relies on external sensors.
Perhaps no other area of the economy has benefited as much from automation as the industrial sector. However, getting a complete, machine vision-driven automation system into a workplace is a long and challenging prospect. Many processes must be undertaken before the system reaches its final destination and be integrated into operations there.
Machine vision systems are incredibly complex. In even the simplest system, hardware and software work together to produce results. Although there are many vital components, one stands out: The lens.