Machine Vision Systems for Robotics and Industrial Inspection

Which Machine Vision System Fits Your Application?

The selection process should not begin with camera resolution or a specific model. Start by defining the information your automation process needs.

Does the system only need to confirm that a part is present? Must it read a code, detect an assembly error, or determine the position of a workpiece? Does the robot only need X and Y coordinates, or also height, tilt, and three-dimensional orientation?

These requirements determine whether you need a compact vision sensor, smart camera, code reader, 2D robot-guidance system, or 3D machine vision solution.

Vision Sensor, Smart Camera, or Complete Vision System?

The product grid includes several system classes. They do not provide the same functions and should not be compared by price alone.

Vision Sensor

A vision sensor combines a camera, image processing, and often integrated lighting in one compact housing. It is designed for clearly defined tasks such as presence detection, contour inspection, color checks, position verification, or basic pass/fail decisions.

The visible ifm and SICK products belong to this category. They are particularly suitable when a standardized inspection task must be implemented without extensive custom programming.

Smart Camera

A smart camera also combines image capture and processing in one device. Depending on the model, it may offer more advanced software tools, flexible inspection sequences, and additional communication options.

The Dobot VX500 is one example in the category. Before purchasing, check which robots, controllers, software environments, and applications the specific camera supports.

Camera-Based Code Reader

A code reader is optimized for identifying barcodes, Data Matrix codes, QR codes, or text. It is usually the appropriate choice when product identification and traceability are the main requirements.

A broader machine vision system may be more suitable when the application must also inspect contours, colors, dimensions, or part positions.

Modular or Complete Robot Vision System

A modular system consists of individually selected components such as a machine vision camera, lens, lighting, processing hardware, and software. It provides greater flexibility but requires more engineering and integration.

A complete robot vision system goes further. It detects a part, calculates coordinates, and sends usable position data to the robot controller. Calibration, object recognition, and robot-guidance software may already be included, depending on the product.

2D or 3D Machine Vision?

A 2D system evaluates contours, colors, brightness, and positions within a flat image. A 3D system also captures height, depth, distance, or spatial orientation.

A 3D system is not automatically the better option. If parts lie flat on a conveyor or in a tray and only vary in X position, Y position, and rotation, 2D vision may be sufficient and more economical.

3D becomes relevant when parts have different heights, are tilted, overlap, or require a spatial gripping position.

When Is 2D Robot Guidance Sufficient?

A 2D robot-guidance system determines the position of a workpiece within a single plane. It typically calculates X and Y coordinates and the rotation angle.

Suitable applications include:

• Pick and place with flat parts

• Parts supplied in trays

• Structured part feeding

• Sorting processes

• Position correction before assembly

• Machine loading with consistent part height

The SICK PLOC2D visible in the category belongs to this product class.

Before selecting a 2D system, determine whether all parts remain on the same plane, whether parts can overlap, and how accurately the gripping point must be calculated. When height, tilt, or spatial orientation varies significantly, a 3D solution should be considered.

When Do Robot Vision Systems Need 3D Technology?

3D robot vision systems are used when the robot requires spatial information. Typical applications include:

• Random bin picking

• Palletizing and depalletizing

• Gripping parts with different heights

• Detecting tilted or rotated objects

• Loading machines from containers

• Height and volume inspection

• Spatial quality inspection

The category includes multiple Mech-Eye models and 3D products from SICK. These variants are designed for different fields of view, working distances, part sizes, installation conditions, and precision requirements.

The correct 3D camera can therefore only be selected after the real workspace, part, and handling process have been defined.

When Are AI-Based Vision Systems Useful?

Traditional machine vision uses predefined rules such as contours, distances, colors, or code patterns. It is often the most practical approach for stable processes with clearly defined inspection criteria.

AI-supported vision can be useful when defects, surfaces, or object shapes vary and cannot be described reliably with fixed rules.

Examples visible in the RBTX assortment include:

• INSPEKTO S70 for visual quality inspection

• robobrain.vision for intelligent object detection

• GuideNOW for AI- and 3D-supported robotic vision

AI is not required for every inspection. Code reading, dimensional checks, defined contours, and straightforward presence detection can often be implemented more simply with rule-based vision tools.

AI also does not replace suitable imaging conditions. If the relevant feature is not visible because of poor lighting, an unsuitable viewing angle, or insufficient image detail, reliable classification may remain difficult.

Which Technical Criteria Matter Most?

Field of View and Working Distance

The field of view defines the area that must be visible in one image. The working distance is the space between the camera and the workpiece.

A larger field of view captures a wider area but can reduce the available image detail for each part. The camera should therefore not be configured for a larger area than the process requires.

For 3D machine vision, also consider the minimum and maximum object height, container depth, possible shadows, robot position, and available installation space.

Resolution

The required resolution depends on the smallest feature that must be detected. Confirming the presence of a large component requires less image detail than detecting a fine scratch or measuring a small edge.

More megapixels do not automatically produce a better result. Higher resolution also creates more data and may increase image-transfer and processing time.

Define:

• The complete inspection area

• The smallest relevant feature

• Whether the feature must be detected, classified, or measured

• The permitted inspection tolerance

• Whether the object moves during image capture

Lighting

Lighting determines which features are visible to the camera. Many compact vision sensors and smart cameras already include integrated lighting.

External lighting may still be required for reflective metal, transparent plastic, dark parts, structured surfaces, or large inspection areas. The lighting concept should be tested with real good parts, defective parts, and permitted product variations.

Software and Interfaces

The vision system must send useful results to the robot, PLC, machine controller, or database.

Before purchasing, check:

• Communication with the robot controller or PLC

• Supported protocols and data formats

• Available robot drivers or plug-ins

• Included software functions

• Additional software licenses

• Calibration tools

• Backup and recipe management

• Options for saving inspection results or images

A technically capable camera may still be unsuitable when the required controller interface or software integration is missing.

When Is a Machine Vision Camera Module Sufficient?

A camera module is not necessarily a complete machine vision system. It initially provides image data. Automated analysis may also require:

• Lens

• Lighting

• Mounting hardware

• Processing unit

• Vision software

• Calibration

• Programming

• Controller communication

Machine vision cameras and USB modules are suitable when a compatible software and control environment already exists or when a custom system is being developed.

For a standardized inspection task, a vision sensor or smart camera may require less integration work despite a higher initial product price.

Which System Fits Which Application?

What Do Machine Vision Systems Cost?

The products in the category range from individual USB camera modules to complete 3D and AI-based systems. Prices should therefore only be compared within similar product classes.

Additional costs may include mounts, protective housings, external lighting, software licenses, calibration, robot programming, and application testing.

The most economical solution is therefore not always the least expensive camera. Total cost depends on how much additional hardware, software, and engineering are required before the system can perform the intended task.

How to Select the Right Machine Vision System

1. Define the exact inspection, identification, or guidance task.

2. Specify the required result: signal, code, measurement, or robot coordinate.

3. Describe good parts, defective parts, and permitted variations.

4. Determine the field of view, working distance, and smallest relevant feature.

5. Decide whether 2D information is sufficient or 3D data is required.

6. Choose between a vision sensor, smart camera, code reader, camera module, and robot-guidance system.

7. Consider part material, color, surface, and lighting.

8. Verify communication with the robot, PLC, or machine.

9. Review software functions and possible license costs.

10. Test the solution with real workpieces and realistic process conditions.

11. Compare total integration effort rather than product price alone.

Frequently Asked Questions About Machine Vision Systems

What Is a Machine Vision System?

A machine vision system captures and analyzes images or 3D data for an automated industrial process. Depending on the design, it may include a camera, lens, lighting, processing hardware, software, and communication interfaces.

What Is the Difference Between a Vision Sensor and a Smart Camera?

A vision sensor is generally designed for clearly defined standard tasks. A smart camera may provide more extensive software and communication functions. However, manufacturers do not always use these terms in exactly the same way.

When Is a 2D Vision System Sufficient?

2D vision is often sufficient when all relevant features are visible on one consistent plane. Examples include code reading, contour inspection, presence detection, and positioning flat parts.

When Is 3D Machine Vision Required?

3D vision is appropriate when height, depth, tilt, volume, or spatial orientation affects the task. Common applications include bin picking, depalletizing, and robot guidance for randomly positioned parts.

Is a USB Camera Module a Complete Vision System?

Not necessarily. A camera module may require additional optics, lighting, software, processing hardware, calibration, and controller integration.

Do I Need a Color Camera?

A color camera is necessary when color is an important inspection feature. Monochrome or infrared imaging may be sufficient for contours, codes, positions, and many presence checks.

Can Any Vision System Connect to Any Robot?

No. Interfaces, communication protocols, coordinate formats, software, and available drivers must be compatible with the robot controller. Robot-guidance applications also require suitable calibration.

When Is AI Useful for Machine Vision?

AI can be useful for varying defects, natural surfaces, or object shapes that are difficult to describe with fixed rules. Traditional machine vision is often simpler for codes, measurements, and clearly defined contours.

How Should I Test a Vision System Before Purchasing?

Test the system with real good parts, typical defects, permitted variations, and difficult edge cases. Working distance, lighting, movement, cycle time, and environmental conditions should be as close as possible to the intended production process.