How Does Embedded Vision Improve Industrial Robots?

Here’s an introduction to embedded vision technology and some of its top applications today.

Embedded vision vs. computer vision

Embedded vision, often known as machine vision, is a manufacturing technology that allows robots to “see” the real world using cameras and sensors. This capability opens up many exciting opportunities in robotic automation, but embedded vision may sometimes be confused with computer vision.

The difference between these two similar technologies is their context. Computer vision is a machine learning algorithm that can process images and recognize specific objects or features. Computer vision is the basis for embedded vision, but embedded vision is specifically used in manufacturing. In contrast, computer vision can be used in various applications.

How embedded vision works

Embedded vision integrates the image processing capabilities of computer vision algorithms into physical robots. The algorithm is trained to recognize certain images, such as a properly assembled unit compared to a defective one. Once successfully trained, it can be integrated into industrial robots on the manufacturing floor.

These robots are equipped with tools to process images in real-time, including cameras and lighting instruments. The embedded vision algorithm processes the live feed from the camera, and the robot acts accordingly.

For example, a robotic arm might use embedded vision to detect defective products on an assembly line in a quality control application. The embedded vision algorithm rapidly analyzes images as the items move past the robot’s camera. It can find a defective product and tell the robot to move that unit to a bin for repair.

How to implement embedded vision

There are various ways manufacturers can implement embedded vision in their robotics and automation systems. Here’s a look at a few of the top applications in the industry today.

1. Quality control

The most popular application for embedded vision in industrial robots is quality control. Embedded vision is the perfect tool for automating this process effectively. Previously, this task had to be done manually. Robots could assemble products effectively but lacked the intelligence and capabilities to verify consistently high manufacturing quality.

Embedded vision changes that. Manufacturers can use robots with cameras to rapidly analyze units throughout the assembly process. Today’s computer vision algorithms are highly adept at detecting abnormalities that indicate a potential production defect.

Applying embedded vision in quality control can result in better products delivered to customers. It can also help manufacturers meet quality standards, such as the highly detailed regulations required for PCBs and other electronic components.

2. Autonomous navigation

An increasingly popular application for embedded vision in industrial robots is autonomous navigation. This tends to be most popular in warehouse settings. For example, order-picking robots might use it to navigate around a warehouse by recognizing QR codes or following painted lines on the ground.

This application uses embedded vision to actively monitor the robot’s surroundings, searching for landmarks that allow navigation. The main benefit of doing this, as opposed to using preprogrammed paths, is the amount of flexibility it enables.

Robots with embedded vision can use visual landmarks, such as QR codes, placed around a warehouse or manufacturing space to navigate any location or travel along any route.

3. Employee safety

Embedded vision also improves robot safety when working alongside employees. Industrial settings move fast, which makes safety a top priority. Unfortunately, accidents can happen in the workplace during a robot’s normal operation simply because the machine is unaware of its surroundings.

Embedded vision allows robots to see the surrounding environment. This can significantly improve employee safety since robots with computer vision can detect the presence of a nearby human, preventing collisions and accidents. Advanced context-aware industrial robots are already being used on assembly lines, where collaborative robots (cobots) work safely with people.

Benefits of embedded vision

Integrating embedded vision into industrial robots opens the door to many benefits for manufacturers, as well as their employees and customers. It can improve flexibility by giving robots the intelligence to navigate without preprogrammed instructions.

This same flexibility applies to other applications, as well. For instance, embedded vision improves the efficiency of the quality control process, allowing manufacturers more flexibility about where they integrate QC checkpoints in the manufacturing process. An added benefit of using embedded vision for quality control is the improved quality that results from consistent analysis.

A well-trained embedded vision algorithm can often recognize product defects much faster than the average person. Since QC is so efficient with embedded vision, manufacturers can consider adding more checkpoints to catch defects earlier. This could lower costs by reducing the amount of resources wasted on defective products. It can also result in more high-quality items making it through the assembly process and into customers’ hands.

Embedded vision also creates a safer workplace in an industry that is increasingly utilizing robotics. Studies by the International Federation of Robotics found that the average density of robots to humans in manufacturing nearly doubled from 2015 to 2021. As these machines become more popular, safety technology will need to be a priority.

Robots can be extremely helpful in the workplace, but they also need technology that allows them to work safely with humans. Embedded vision gives them the intelligence and capability to help keep employees safe on the job.

Innovating industrial robot technology

Embedded vision is transforming industrial robotics. It unlocks new possibilities in numerous industries by giving robots the ability to analyze their surroundings using sight. There are many ways for businesses to implement embedded vision in their robots, from enhanced autonomous navigation in automated warehouses to smart robotic quality control.

Taking the leap on this innovation can lead to a safer, smarter workplace that operates efficiently while minimizing waste and maximizing flexibility. Businesses that adopt embedded vision can reap the many benefits of this AI technology and be part of the future of industrial robotics.