Robotics have simplified many processes for decades, but recent advancements are allowing businesses to use robots in far more applications than ever before. One such innovation is machine vision.

Machine vision was developed in the 50s and has seen widespread use in manufacturing since the 80s. But in today’s world, companies are using it across many industries in varied roles. More advanced cameras and more powerful processing have led to it paving the way for new and exciting technologies.

In several different spheres, modern machine vision is changing the way we do things.

What Is Machine Vision?

Essentially, machine vision is the concept of giving machines eyes. It uses a camera to observe the environment and then processes the images to dictate the machine’s actions. The ability to “see” and process the world in real-time dramatically expands the horizons of what robots can do.

It’s easy to confuse machine vision with computer vision. Not only do the terms sound a lot alike, but they are closely related. There are, however, important distinctions between the two.

Computer vision refers to programs or devices that scan and analyze things like photos, videos, or digital images. Computer vision can process more kinds of images than machine vision, which relies on cameras, but machine vision takes the process one step further. Whereas computer vision offers insights regarding a picture, machine vision uses these insights to perform a task automatically.

Machine vision can vary quite a bit depending on the specific use. Still, these systems generally include a camera rig, including proper lighting equipment, a processor, and some form of output.

The possibilities provided by machine vision are staggering. But how are companies using it today?

Quality Control

One of the most prominent uses of machine vision is quality control. Traditionally, quality checks have been performed by people, even in highly automated facilities. But the human eye can only detect so much, and even experts can get tired and make mistakes.

Robots offer two main advantages here: they can’t get tired, and they can process more information at faster speeds. With machine vision, manufacturing plants can apply the benefits of robotics to the complex area of quality inspection.

Companies can use vision-enabled robots beside employees to ensure there are no slips in the quality inspection. Alternatively, they could leave the entire task to machines, allowing human workers to focus on more abstract tasks a robot can’t do. Either way, machine vision is offering a vast improvement in both speed and quality in the assembly process.

Robot Guidance

A clear advantage of allowing robots to see is improving the way they move. Without vision, machines can still travel, following a programmed path. But these run the risk of colliding with unforeseen obstacles, not to mention the disadvantage of only being able to follow a set track.

Robot guidance is the foundation for self-driving cars that, once perfected, can significantly reduce traffic accidents. As processing power increases, machine vision will be able to recognize more objects more quickly, bringing the future of fully automated vehicles closer to the present.

Machine vision can help guide robots other than cars as well. Agricultural machines like harvesters can operate on their own with machine vision, allowing farmers to attend to other matters while these machines do their job.

Inventory Management

Managing warehouse inventory is a task that can see a lot of improvement from more advanced robotics. Traditional machines can grab and move items just fine, but can’t tell what they’re grabbing or decide where to put it, limiting their usefulness. Machine vision allows inventory robots to reach their full potential.

With integrated camera systems, machines can read barcodes and labels. This ability allows them to differentiate between different packages or items and determine where they need to go. These robots can then use machine vision to move things to the correct location.

Mistakes in inventory management can cause serious repercussions further along the logistics chain. Misplaced items can result in manufacturing errors or customers not receiving the proper packages in time. Automating the inventory process can help reduce these errors, and machine vision makes this automation more viable.

Medical Automation

As an area where accurate readings are critical, the field of medicine has a lot to gain from machine vision. While doctors are still necessary for proper diagnosis, machines with vision can offer helpful initial analysis, and help speed up the whole process. Machine vision can see anomalies undetectable to the human eye and, unlike traditional medical equipment, can make sense of these readings.

Many conditions are time-sensitive and require a quick diagnosis so medical staff can treat them as soon as possible. As machines can see far more than humans, intelligent machine vision systems can make speedy analyses, potentially saving the lives of patients.

It’s no wonder why some experts expect the machine vision market to grow to $30.8 billion by 2021. Machine vision allows robotics to see use in a vast array of fields, stretching the limits of what’s possible.

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