Over the past few years, LiDAR data has quickly become one of the most reliable foundations for creating precise and accurate 3D models. Industries like mining, construction, and infrastructure are using these models to conduct routine inspections, make safety determinations, track the change of assets over time, and support project planning. The outputs professionals get from 3D models made with LiDAR data include detailed digital twins, accurate 2D and 3D measurements, the ability to pinpoint defects within assets, exporting data to common 3D point cloud formats, and merging multiple georeferenced models to track changes over time. The quality of the model is key to its usefulness. If the data isn't accurate, it may not represent the real world well enough to offer valuable insights.
This article covers findings from tests performed by experts at FARO (formerly GeoSLAM) and the Flyability product team that highlight the differences between models processed using FlyAware and FARO Connect.
The Elios 3 comes with Ouster’s OS0-128 Rev 7 LiDAR sensor and the ability to perform SLAM (simultaneous localization and mapping), which means it can create 3D models in real time while in flight. After the flight, users can process the LiDAR data they collected with FARO Connect to create precise, accurate 3D models. The 3D Live Model and the post-processed model have distinct uses and should not be seen as the same kinds of 3D models. While the 3D Live Model can be used during a mission for navigation, route planning, and verifying scan coverage, the post-processed model you make with FARO Connect can provide an accurate point cloud.
Global accuracy in 3D modeling relates to the distance between two points in a point cloud, where the object cannot be viewed from a single position. Georeferenced accuracy is global accuracy plus inaccuracies caused by the alignment method. Drift is a term used in 3D modeling to describe the cumulative decrease in accuracy over the duration of a capture. For example, the error on a 30m measurement is likely to be smaller than the error on a 300m measurement due to drift.
To compare and evaluate the global accuracy and georeferenced accuracy of the Elios 3’s point clouds, identical captures were processed using both FlyAware and FARO Connect. The tests were conducted in an industrial factory. When assessing the accuracy of any system, a second measurement system must be used to provide the benchmark value (i.e., the control). The industry standard is to use either a Total Station or a Terrestrial Laser Scanner as a control because their accuracy exceeds that of a mobile mapping solution. In this test, a Terrestrial Laser Scanner was used as the control. It took more than six hours to acquire the data, compared to 8.5 minutes for the Elios 3.
The test environment was the Blue Factory in Fribourg, Switzerland, consisting of 12 rooms of varying sizes separated by several doorways. 15x Retroreflective Diamond Grade 3M targets were placed evenly around the test environment. Three scans were carried out with the Elios 3 to capture LiDAR data for testing, all following the same approximate flight path to ensure consistency between the results. All scans started and ended in the same location to ensure that the data capture loop was closed. Best practice for SLAM data capture was maintained by performing loops within the capture and entering doorways sideways to ensure good visualization when moving into new environments.
The three scans had an average flight time of 8 minutes and 30 seconds over a ~450 meters flight path. Datasets processed using FARO Connect averaged 108 million points per scan while datasets processed using FlyAware averaged 21 million points per scan. To ensure that the test was representative of what an end user can expect from the system, the GeoSLAM processing was carried out using the standard Flyability processing parameters found in FARO Connect. The data was not reprocessed by any other means, neither was it decimated nor filtered. The FlyAware Live Model was processed onboard the Elios 3. It was neither reprocessed, filtered nor decimated.
As a post-processing step, an extraction tool was run to identify the 15x targets in both the Elios 3 data and the TLS data. Once the targets were identified, the tool extracted the centroids of the targets to provide 15x centroids for both the Elios 3 and the TLS data. The centroids of the TLS data were used as Control Points and the Elios 3 centroids were used for comparison.
To assess the global accuracy of the Elios 3, distance measurements were carried out and the Elios 3 data was compared against the TLS control data. The steps included measuring distances between pairs of centroids, finding residuals, calculating RMSE, and finally finding the mean error. The results showed that processing using FARO Connect improved global accuracy by 5.2 times compared to processing using FlyAware alone. The average accuracy of 182 mm (7.2 inches) from the FlyAware Live Model does not make it fit for applications requiring higher precision.
In the georeferenced accuracy assessment, the Elios 3 point cloud was aligned to the reference model around the take-off location. This simulates procedures followed during missions in inaccessible areas. The results showed that point clouds processed using FARO Connect were 5.9 times more accurate than those processed using FlyAware. This can be attributed to the higher system drift accumulated during FlyAware processing, which was 7.42 times the value produced by FARO Connect.
The horizontal offset between the FlyAware point clouds and the TLS control at distances of over 75m from the take-off location clearly demonstrates the impact of drift. Green represents the Riegl VZ400 TLS control, white represents the Elios 3 point cloud processed using FARO Connect, and yellow represents the Elios 3 point cloud processed using FlyAware.
Overall, the test results show that the Elios 3's point clouds processed with FARO Connect produce high accuracy and lower drift compared with the point clouds processed using FlyAware. By utilizing FARO Connect, the Elios 3 is able to meet survey requirements with minimal system accuracy of 35 mm (1.38 inches).
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