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 changes in assets over time, and support project planning. The outputs from 3D models made with LiDAR data include detailed digital twins, accurate 2D and 3D measurements, defect detection, exporting data to common file formats, and merging multiple georeferenced models.
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 SLAM capabilities, allowing it to create 3D models in real time while in flight. After the flight, users can process the LiDAR data with FARO Connect to create precise models. The 3D Live Model and post-processed model serve different purposes; the Live Model is used during a mission for navigation, while the post-processed model provides an accurate point cloud.
Global accuracy relates to the distance between two points in a point cloud, while georeferenced accuracy includes inaccuracies from alignment methods. Drift refers to the cumulative decrease in accuracy over time due to errors accumulating as the scanner moves.
To compare the global and georeferenced accuracy of the Elios 3's point clouds, identical captures were processed using both FlyAware and FARO Connect. A Terrestrial Laser Scanner (TLS) was used as the control for the tests. The factory environment provided a representative setting for testing, with 15x retroreflective targets placed around the area.
Three scans were carried out with the Elios 3, following the same flight path to ensure consistency. The data was processed using standard parameters found in FARO Connect. An extraction tool was run to identify the 15x targets in both the Elios 3 data and the TLS data. The centroids of the targets were compared to assess accuracy.
The results showed that processing using FARO Connect improved global accuracy by 5.2 times compared to FlyAware. The average accuracy of the Live Model was 182 mm (7.2 inches), which is not suitable for many applications. The Cloud-to-Cloud assessment demonstrated how the Elios 3 can be used to map and georeference inaccessible environments.
Georeferenced accuracies showed that point clouds processed using FARO Connect were 5.9 times more accurate than those processed using FlyAware. This difference can be attributed to the higher system drift in FlyAware processing. The images clearly show the horizontal offset between the FlyAware point clouds and the TLS control at distances over 75m from the take-off location.
In conclusion, the test results show that the Elios 3’s point clouds processed with FARO Connect produce high accuracy and lower drift compared to those processed using FlyAware. This makes the Elios 3 suitable for meeting survey requirements with minimal system accuracy.
Traction Sprayer,Traction Pneumatic Sprayer,Traction Compound Sprayer,Sprayer Traction Control
Gongzhuling Huaxi Agricultural Machinery Manufacturing Co.LTD , https://www.hxzbjx.com