1. Observe
The camera receives existing light or light from its own projector or laser.
Knowledge · 3D cameras
What is an industrial 3D camera and how does it work?
An industrial 3D camera measures the distance to visible points on a product or in a work area. The resulting depth map or point cloud allows a vision system to determine height, shape, volume, position and orientation for measurement, inspection and robot guidance.
The basics
A distance for each visible measurement point
A normal 2D image describes where light, dark or coloured pixels are located. A 3D camera adds distance information for visible surfaces. After calibration, software can convert that data into height, dimensions, volume, or the position and orientation of a part.
The camera does not see hidden internal geometry. It measures only surfaces that return enough light from the selected viewing direction and can be observed by the measurement principle being used.
From capture to depth
How 3D capture works at a high level
The underlying physics differs between cameras, but the processing chain is similar.
2. Determine distance
The system derives distance from image disparity, pattern deformation, travel time or triangulation.
3. Form data
The measurement becomes a depth map, point cloud or height profile.
4. Decide
Software calculates a dimension, checks a limit or guides a robot.
Output
Which data does a 3D camera produce?
Depth map
A grid in which each valid pixel contains a distance. Useful when software combines image position and depth.
Point cloud
A set of measurement points with X, Y and Z coordinates that describes visible surfaces in space.
Height profile
A cross-section or series of cross-sections, often built while the product or sensor moves.
RGB-D
Depth registered to colour or intensity information. RGB-D is a data combination, not a separate measurement principle.
Applications
When does an application need depth?
3D adds value when the process decision depends on height, shape, volume or a position outside one fixed plane. For presence, colour, codes or outlines in a plane, 2D may be simpler.
- Robot guidance: locate parts with varying height or orientation.
- Measurement: check height, flatness, gaps, welds or sealant beads.
- Volume: determine fill level, contents or stack height.
- Inspection: identify deformation, missing geometry or dimensional differences.
What a 3D camera does not solve automatically
A depth sensor does not make difficult surfaces measurable by itself. Very dark, glossy or transparent parts, strong ambient light, motion and surfaces hidden by other parts can cause gaps or errors.
An attractive 3D image is not yet a reliable process decision. Calibration and software must translate the measurement data into a repeatable dimension, inspection outcome or robot position.
Products
Browse cameras once the measurement task is clear
The product category helps you compare available industrial 3D cameras. Use it after establishing which data and working volume the application needs.
Measurement principles
Different ways to determine depth
Stereo
Determines distance from the difference between two images, optionally with projected texture.
Structured light
Measures how a known light pattern deforms across the surface.
Time of flight
Derives distance from the travel time or phase of emitted light.
Laser triangulation
Measures the position of a laser line and builds a profile or height image during motion.
Practical examples
The measurement outcome creates the value
Container or pallet: a point cloud helps a robot find a reachable part or free position.
Conveyor: a height image reveals volume, deformation or missing geometry.
Weld or sealant bead: a profile makes width, height and interruptions measurable.
From depth data to an action
The camera supplies measurement data. Vision software removes invalid points, relates the data to a coordinate system and then calculates the outcome required by the process.
That outcome may be a dimension, pass or fail result, volume estimate or robot position. The PLC or robot uses this outcome and does not always need the complete point cloud.
Practical trial
When is the depth measurement suitable for production?
Evaluate the complete measurement chain using representative parts and predefined limits. Acceptance concerns the process result, not only a visually clean point cloud.
Representative samples
Test accepted, rejected and borderline cases from the actual product mix. Include relevant surfaces, colours, shapes and orientations.
Actual conditions
Vary measurement distance, part position, motion, ambient light and the contamination that may occur during normal production.
Valid measurement data
Define where valid depth points are required and how many missing or incorrect points the calculation may contain.
Repeatability and reference
Measure the same parts repeatedly and compare relevant dimensions with an agreed reference method. Derive the tolerance from the process limit.
Cycle time
Measure capture, transfer, processing and communication together at the highest agreed line load. Include any motion or multiple captures.
Fault handling
Test missing data, low measurement quality, contamination and loss of calibration. The system must then perform a controlled warning, stop or handling action.
Business case
Which inputs determine the value of 3D?
A 3D camera creates process value only when its measurement result demonstrably affects manual work, errors or downtime. Use data from your own line and record assumptions separately.
Current work
Measure manual measurement or inspection time, operator interventions, staffing per shift and time spent recording data.
Cost of deviations
Collect quantities and costs for rejects, material loss, rework, returns, claims and line stops that the 3D measurement can influence.
Production conditions
Record volumes, cycle time, batch size, product mix, changeover time and available maintenance windows.
Investment and ownership
Include the sensor, controller, mechanics, shielding, calibration, software, integration, validation, training, cleaning, spares and licences.
Calculation model
Annual process value = avoided manual hours + avoided cost of errors and downtime + contribution from usable additional capacity − additional ownership and maintenance cost. Compare this with the total investment and state which process data still has to be established in a trial.
Frequently asked questions about 3D cameras
Does a 3D camera always measure colour?
No. Some systems provide only distance or intensity. RGB-D systems register depth to colour.
Does a 3D camera see the complete shape?
Not from one viewing direction. Hidden surfaces require another position, multiple cameras, or movement of the sensor or product.
Is 3D always more accurate than 2D?
No. 3D adds depth, but achievable measurement quality depends on the principle, geometry, surface and conditions.
When is 2D sufficient?
When contrast, colour, a code or an outline in one known plane fully answers the process question.
From a need for depth to an appropriate solution
First define which height, shape, volume or position the process needs. Then compare measurement principles or available cameras with that purpose in mind.