How Do Robot Cameras Recognize Parts

March 21, 2022
KUKA Systems Corp. North America
News

Summary

Vision Systems Let Robots See What They Are Doing — Vision Systems Permit Robots Run across What They Are Doing

For nearly a century, manufacturers have adult and applied robotic equipment to heave speed, accuracy and repeatability in a wide variety of tasks. In the last 40 years, vision engineering science has enabled robots to view a known workspace, detect objects and perform desired actions. Together, the robot, programming software and imaging hardware increment productivity and consistency. Vision systems expand a robot's range of applications with increased flexibility to handle greater variation in parts and processes.

Basic vision system functions

Robotic vision systems provide four basic functions: positioning, inspection, measurement and code reading. The most common is positioning, namely determining an object'south location and reporting it to the robot controller. The controller typically then directs the robot to pick up the object and place it somewhere else. Inspection functions view an object to place missing or defective features. Users also tin can program a system to measure an object'due south dimensions, area and volume.

Finally, a vision system can decode and read one-dimensional (1D) and 2-dimensional (2D) codes to provide optical grapheme recognition (OCR) and verification (OCV). OCR recognizes alphanumeric characters by comparing to a library of character patterns, while OCV verifies that an alphanumeric character is complete.

Levels of robotic vision

Introduced in the 1980s and early 1990s, the first commercial robotic vision systems performed 2D part recognition, in which a photographic camera acquires images of objects across X and Y planes. These systems provide two-dimensional feedback to guide basic robotic functions and are well-nigh oft used in simple applications that involve batches of very similar parts in pre-determined locations.

A 2D vision system'due south recognition and location capabilities eliminate the demand for an operator to handle a role and put information technology in a fixture. With 2d vision, robots tin sort and organize objects. Because of their simplicity and thorough development over fourth dimension, 2nd systems are piece of cake and toll effective to integrate and operate.

2D vision technology works best with strong, contrasting lighting and parts that lay relatively flat with limited overlap, such as in simple automatic option-and-identify operations. Variably shaped parts, dim or uneven lighting weather condition and advanced handling operations also tin challenge the effectiveness of 2D robotic vision systems.

For more-complex tasks, 3D vision uses complex imaging technologies – such every bit multiple cameras – to detect X and Y function locations as well equally Z (height) measurements and angles in all iii planes, enabling determination of an object'south shape and volume. A 3D vision system tin adjust to overlapped and stacked items in and so-called "semi-structured" applications that involve parts at dissimilar heights, layers and angles. Applications mainly focus on positioning, measurement and inspection.

The flexibility of 3D vision systems enables them to adapt to changes in a process, operate accurately under poor lighting conditions and fully exploit the capabilities of six-centrality robots. These systems recognize parts, decide distances and calculate trajectories in 3D space, enabling a robot to optimize the path on which it moves an object.

These 3D robotic vision systems expand the range of robotic applications beyond simple part location. With integrated 3D cameras, avant-garde robots can inspect components, construct intricate assemblies and adjust dynamically to varying parts and locations. The sole tradeoff is added complexity and expense. To determine whether an application requires 3D vision or if a 2D setup volition meet the needs of a production line, manufacturers can consult with the robot manufacturer or a system integrator to assess the awarding and programme for the best arroyo.

Robotic camera systems

Depending on what a vision system must accomplish, information technology uses ane of 3 primary camera placements. Stationary setups mount the camera where it tin can view the workspace, at the expense of limited operation flexibility. Alternately, a robot-mounted camera provides enhanced flexibility and enables coverage of a large expanse, but cycle times may increase to allow software to process input from the camera before directing the robot'southward next move.

In a 3rd arroyo, a stock-still-mount camera observes the robot every bit information technology carries a part, perhaps treatment and placing a slice of sheet metal. The robot picks up the part randomly with a suction-cup gripper. The photographic camera and then determines the position of the sheet metal on the gripper and software directs the robot to place the part precisely where desired.

Camera environment and engineering science

2nd applications must depend on the coverage area of the camera lens and lighting that generates sufficient contrast for articulate part identification. Unlike lighting techniques, such every bit ring lights or backlight, may produce optimum results depending on the part and its surroundings. 3D imaging can use a variety of camera processes, including electronic scanning or snapshots.

Object detection and imaging technologies can include structured sensors that clarify the reflection of calorie-free projected onto a part so they can read function dimensions. Time-of-flight cameras project infrared light onto an object and measure the time required for the light to reflect back to the photographic camera so they can determine depth information.

Software

Robotic vision applications use software that processes a camera prototype so directs the action of the robot based on visual information. Dominion-based software stores, sorts and uses information following rules developed by humans. The system uses the rules to interpret and act on visual data from a camera. Some software packages use deep-learning technology that utilizes bogus intelligence (AI) and machine learning to accomplish tasks such every bit object detection and recognition.

Full-featured, flexible 2D and 3D robotic vision

Integrated systems embedded on robots tin offer powerful tools for 2D object recognition, reading bar codes and performing OCR and OCV. The vision tools locate, inspect and read codes on stationary or moving parts. Systems such every bit KUKA.VisionTech are engineered to exist easy to integrate, access and apply.

With a high-quality photographic camera in an IP 67 housing, KUKA.VisionTech supports a broad variety of robot operations, even in unstructured environments, for use in applications that range from fast moving consumer goods to nutrient. Code recognition capability simplifies product traceability, which can be essential for sustainability or quality control. At the same time, the organization enables manufacturers to safeguard product output and reduce costs.

When information technology comes to 3D visions systems, 3D stereo cameras have had a huge impact on the advancement of robot vision system technology. They allow robots to recognize parts–not just their location, but also their orientation. With such systems, KUKA successfully automates the highly challenging bin-picking procedure. The 3D stereo camera/vision system captures a office image and transfers information technology to software, which then uses the images to excerpt data representing viable parts that the robot can pick. From the prototype, the software rates which part is in the optimal selection position or relatively close to it, then sends decisions to the robot.

Choosing a robotic vision system

Robotic vision adequacy has evolved from simple part recognition to fast, flexible, complex sensor systems. Earlier manufacturers add vision capabilities, they should consider what their systems must contribute to production operations and select technology that fully meets those needs. To choose the most efficient, cost-effective arrangement–and one that seamlessly interfaces with various types of cameras–rely on guidance from a robot manufacturer such as KUKA or a system integrator.

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Source: https://www.automation.com/en-us/articles/march-2022/vision-systems-let-robots-see-what-they-are-doing#:~:text=The%20robot%20picks%20up%20the,the%20part%20precisely%20where%20desired.

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