GeoSLAM Connect Software

Create clean, georeferenced point clouds automatically with GeoSLAM Connect

Powered by the world's leading SLAM algorithm, GeoSLAM Connect provides a way to create clean, georeferenced point clouds automatically. Visualize data in the 3D viewer and immediately gain insights from the point cloud from different color modes. Apply an array of additional filters such as outlier, noise, thinning or transient for an even cleaner dataset. Finally, utilize automated pre-built workflows to get the best out of the data or prepare it for third party software with a range of export options.

GeoSLAM Connect comes as standard with all ZEB scanners.

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  • Value
  • Features

Business Value of GeoSLAM Connect

Be in control of data collection and never be sat waiting for results again.
An intuitive interface makes it easy to view multiple point clouds simultaneously.
Data is processed using GeoSLAM’s next generation SLAM algorithm.
Import multiple .geoslam files into Connect and the scans will be processed in the order they were imported. The size of the queue can be defined by the user.
Pre-defined workflows for common data capture scenarios.
Export point cloud data in a range of formats, including LAS, PLY, TXT, and E57.
Take GeoSLAM data into 3rd party software’s such as Revit or ESRI.

Create clean, georeferenced point clouds automatically with GeoSLAM Connect

RGB Colorization

RGB colorization is achieved using the ZEB Vision accessory with the ZEB Horizon. The workflow is divided into four simple processes: Process SLAM, Image Stitching, Image Positioning, and Colorization. These procedures can be completed within the GeoSLAM Connect interface without the need for separate geoscripts. Users can calibrate the ZEB Vision hardware from within Connect.

Data Classifiers

GeoSLAM Connect has a range of filtering tools to help users get the best results from their data. These include outlier removal, surface noise reduction and removal of unwanted points, all of which make point clouds look cleaner and more defined. All these tools are accessible within the Connect interface and can be applied to any dataset.

Reflective Targets for Georeferencing and Alignment

Automatically georeference point clouds using reflective targets. These targets are positioned throughout the scanned area on known points and are detected during the scanning process. In GeoSLAM Connect, these targets are identified and matched with control points to locate the point cloud in the real world. Additionally, align two-point clouds using common reflective targets captured within the scans. Targets will be automatically found in the scanned areas and used to align the point clouds in Connect.


Horizontal and vertical slices can be taken from any location within the point cloud. Horizontal floor slices can also be automatically taken at a given height above the floor as defined in the processing stage.

Change Detection

Mostly used in the construction industry, multiple point clouds can be compared and any areas that have changed are automatically highlighted. Point clouds can also be compared with CAD models – for instance to track progress on a construction site – and PDF reports can be generated to present this information.

SLAM Environmental Pre-sets

Common data capture scenarios, such as UAV, outdoor, indoor, linear, and vehicle, have been characterized in Connect and data processing pre-sets for each environment have been defined. These can be selected at the beginning of the data processing stage allowing this process to be highly simplified.

Stop and Go for Georeferencing and Alignment

Known control points are captured during a scan and automatically compared and matched to the associated coordinates during the processing stage in Connect. A rigid and/or non-rigid adjustment can be made to the dataset and an accuracy report is exported, highlighting how successful the transformation was. Users can now view and manipulate the processing parameters to ensure a more accurate match between points. In addition, common static points are captured during several scans meaning that these datasets can be automatically aligned. A single point cloud is then exported as if the data was captured in a single scan.

Manual Alignment

Align multiple scans using a combination of manual and automatic processes. This workflow can be performed on two or more scans in the same project. Users have a choice to export the aligned scans separately or as a single merged point cloud.

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