Integration of Vision Systems in Industrial Robotics
Industrial robotics plays an essential role in modern manufacturing. For many years, fixed automation was the standard in numerous industrial settings. Today, flexible and adaptive systems are the key to manufacturing many goods.
In this article, we'll discuss how integrating 2D and 3D vision systems with robot controllers has contributed to the rise of pick-and-place and adaptive manufacturing. If you're a Robotics Technician or someone interested in industrial robotics, here's what you need to know about machine vision.
Fundamentals of Machine Vision
Two different types of vision exist in robotics: machine vision and computer vision. Machine vision is a system that captures images of the environment around the machine and processes these images while seeking specific patterns for object detection. Machine vision is limited and can only process specific information. It requires flat images that show width and height but no depth.
Computer vision is a field of AI that processes and analyzes visual content, allowing the computer to "see" a field almost as a human would, with many moving parts and complex relationships between objects in the environment.
The key components of various vision systems in robotics include:
- Vision sensors
- Lighting systems
- Processing units
- Image processing software
- Communication interfaces
Vision systems are typically required for robotics where elements in the environment are random. Having the ability to "see" what is happening in the environment around a machine improves its adaptability, producing reliable outcomes in industrial processes.
2D Vision Systems
2D cameras function by capturing images in two dimensions. These cameras produce flat images that enable the machine to read bar codes and evaluate surface quality. Industries that typically use 2D vision include packaging facilities and electronics manufacturers.
2D systems are more cost-effective than 3D systems, and because of their simplicity, they often operate faster as well. However, they have certain limitations:
- 2-dimensional only: 2D systems can't measure depth or volume, so they're not suitable for complex or uncontrolled environments.
- Lighting sensitivity: Variations in environmental lighting can adversely affect image clarity and thus effectiveness.
3D Vision Systems
3D vision systems capture data along three axes (width, height, and depth), allowing robotic systems to understand their surroundings in three dimensions. 3D machine vision relies on complex software to stitch together images that measure an object's size, shape, and position—much like humans would.
There are many benefits to 3D vision in robotics, but the primary advantages are that it lets robots perceive depth and recognize complex objects. This is especially useful in bin picking and unpacking pallets.
Vision-to-Robot Interface Architecture
The vision-to-robot interface enables robots to find and track parts that are not in fixed positions. A typical system includes three main components: the vision sensor, the vision processor, and the robot controller. The camera or 3D depth sensor captures images of the area before the images are processed. This system must be finely calibrated to ensure a machine understands an object's location relative to the machine itself.
Communication Protocols and Data Exchange
Well-designed communication protocols ensure fast, accurate machine movements. In a vision-guided system, the vision processor sends data to the robot controller. The controller uses this data to decide where and how to move.
Speed and timing matter because robots react in real time to objects in the environment. Small delays may lead to problems, especially in conveyor tracking. Poor communication performance can result in missed opportunities and errors. Consistent formatting is essential to reduce programming complexity and improve reliability.
Dynamic Pick-and-Place Operations
Vision enables machines to remain productive in adaptive environments where there are moving conveyors and randomly oriented parts. The machine begins with an image capture, moves to object detection, calculates positioning, and then moves in response to objects.
For machines with vision systems, there are many benefits over traditional fixed automation, including improvements in speed and efficiency. Additionally, these systems can be adapted to a wider range of manufacturing and industrial purposes.
Manufacturing Applications
Vision-guided robotics can be used in assembly and quality inspections as well as machine tending. AI and machine learning play important roles in advanced vision systems, and the relevant manufacturing applications are expected to grow.
Integration Challenges
Although vision systems have opened up a whole new world of efficiency in manufacturing, many factors can create challenges in real-world environments:
- Lighting variability and environmental noise: Many machines perform best in controlled environments. Lighting variability and environmental noise create confusion in vision systems, leading to errors.
- Maintenance: Machines require ongoing maintenance to continue functioning efficiently and accurately.
- Trade-offs between processing speed and accuracy: Improvements in one area can sometimes cause problems in another. Operators must find the perfect balance between speed and accuracy—even when working with machines.
- Cybersecurity: Connected systems can be vulnerable to outside attacks and must be protected with IT security. This is an ongoing problem for any industrial facility that uses computers in connected systems.
How to Get Started as a Robotics Technician
If you're interested in industrial robotics and want to know more about how to get started as a Robotics Technician, begin by enrolling in a program that teaches what you need to know about the latest robotics technologies. A quality certificate program will give you what you need to enter this exciting field. Contact us at 1-888-553-5333 to speak to one of our Program Consultants.and to learn about our Robotics Technician Training Program today.