FARO Connect

SLAM process

The SLAM workflow allows you to fine-tune processing parameters for demanding capturing conditions. After the initial processing with standard parameters, you can use this workflow to adjust the settings and run SLAM again if the result was not satisfactory.

Alignment

The alignment workflow enables the alignment of multiple point clouds by providing various tools for manual selection and alignment of common user-selected points between scans. A fine alignment procedure is also available and requires that all required scans are accurately aligned at the start of the procedure.

Analysis

There are three analysis workflows for the project dataset, depending on the desired output results: 

Detection of changes: 
Compares point clouds from scans of the same location at different points in time to highlight differences. Objects or surfaces in the output are colored to visualize the detected changes.

Floor slices: 
Creates a scaled PNG image of a slice through the point cloud at a specified height above the ground.

Static Scans with Flash: 
Analyzes Orbis scans and automatically creates static scans at the locations where the scan person stopped. These scans are enriched with flash and color data.

Registration

Five registration workflows allow you to easily align two data sets: 

Reflective Target Alignment, Reflective Target Georeferencing & Stop and Go Alignment: 
Utilize a rigid transformation to align the point cloud to the control points of the reference scan.

Stop and Go georeferencing workflow: 
Can use a rigid or non-rigid transformation by reprocessing the original data with the SLAM algorithm to match the trajectory to the control points.

Filters

Once you have processed the data and confirmed the output, you can apply additional filters to further reduce and cleanse the data. The following workflows are available for this purpose: 

Noise: 
Removes protruding data points on flat surfaces, ideal for environments with such features as walls.

Outliers: 
Removes outliers that can be caused by various factors such as rain or dust.

Area: 
Removes less dense and inaccurate points furthest from the scanner based on their distance from the trajectory

Thinning: 
Reduces point density uniformly to reduce the thickness of scanned surfaces based on a user-defined grid method.

Temporary: 
Identifies temporary points created by movement of people or vehicles during detection.

Vision tools

You can use the image processing tools to further optimize imported scans: 

Stitch Vision Images: 
Generates panoramic images from the scan images and creates a timing file to calculate the camera positions.

Calculate Vision Camera Positions: 
Calculates the exact camera position and orientation for aligning images and point cloud data.

Colorize Cloud Using Vision: 
Extracts color information from the images and adds it to the point cloud data to create a colorized .laz file with RGB information.

Export

Users can export project artifacts in various formats to import them into other applications such as FARO SCENE: 

Point clouds: 
Exported in .laz format, compatible with .e57, .las, .laz, .ply or .txt.

Control points / reference points: 
Can be exported as .txt.

Static scans: 
Exported as .e57 structure, suitable for import and analysis in FARO SCENE.