Note: The first two sections of this article (the Introduction and Why We Performed These Tests) are identical to the ones in the previously mentioned article. If you've already read that white paper, we recommend starting from the Defining Our Terms section below.

TEST RESULTS OVERVIEW

Introduction

In recent years, LiDAR has become one of the most reliable tools for creating accurate and precise 3D models. Industries such as mining, construction, and infrastructure use these models for inspections, safety assessments, asset tracking, and project planning.

Professionals in these fields benefit from detailed digital twins, accurate measurements, defect identification, and the ability to export data in common formats like *.e57, *.las, *.laz, and *.ply. They also use multiple georeferenced models to track changes over time.

The quality of the 3D model is essential for its usefulness. If the data lacks precision and accuracy—terms with specific definitions in 3D modeling—it may not accurately represent the real world, limiting its value.

This article presents findings from tests conducted by GeoSLAM and Flyability experts, comparing the system precision and local accuracy of 3D models created using the Elios 3 with GeoSLAM Connect to leading mobile mapping systems like the ZEB Revo and ZEB Horizon.

Why We Performed These Tests

Flyability’s Elios 3 features Ouster’s OS0-32 LiDAR sensor and SLAM technology, enabling real-time 3D model creation during flight. After the mission, users process the data with GeoSLAM Connect to generate precise and accurate models.

The 3D Live Model is used for navigation and route planning during missions, while the post-processed model offers a high-quality point cloud. This combination enhances the usability of the Elios 3 in confined spaces.

However, potential users may wonder about the impact of drone vibrations or environmental factors on model quality when using the Elios 3 with a LiDAR payload. To address these concerns, we conducted a thorough analysis of system precision and local accuracy with the Elios 3 and GeoSLAM Connect.

Defining Our Terms: Precision and Local Accuracy in 3D Mapping

In 3D modeling, accuracy refers to how closely a measured value matches the true value. For example, if a point cloud shows a distance of 100mm but the actual measurement is 500mm, the model is not accurate.

Local accuracy relates to the consistency of measurements within a single view, such as the dimensions of a room. This article focuses on local accuracy results for the Elios 3 and GeoSLAM Connect.

Precision refers to the repeatability of measurements. If five measurements of the same distance yield the same result, the model is precise. Precision is crucial for applications where small variations matter, such as in construction.

Understanding these terms helps in evaluating the performance of 3D models and their suitability for different industries.

System Precision and Local Accuracy Assessments with the Elios 3

To evaluate the Elios 3’s performance, GeoSLAM experts and Flyability engineers conducted:

• A Plane-to-Plane analysis for local accuracy
• A Range Noise evaluation for system precision

Establishing a Control

For accurate testing, a control model must be more accurate than the system being tested. In this case, a Riegl VZ-400 TLS served as the control, offering a benchmark with an accuracy of 5mm at 1-sigma.

Data Collection

Both the Elios 3 and the Riegl VZ-400 were used to capture data from a planar indoor environment. The Riegl data formed the reference model, which was then compared to the Elios 3 data processed with GeoSLAM Connect.

Aligning the Point Clouds

The Elios 3 point cloud was aligned to the reference model using PolyWorks|Inspector MRS2019 IR3. This involved manual alignment followed by an automated Best-Fit algorithm to minimize differences between the two datasets.

Assessing Local Accuracy

A Plane-to-Plane comparison was performed, calculating the Normal Distance between planes in the Elios 3 data and the reference model. Results showed a mean absolute distance of 8mm, with all values within +/- 16mm.

Assessing System Precision

Range Noise analysis revealed a mean standard deviation of 8mm, indicating good system precision. The results confirm that the Elios 3 with GeoSLAM Connect produces highly accurate and repeatable 3D models.

Conclusion

The Elios 3 with GeoSLAM Connect demonstrated strong performance in both local accuracy and system precision. Compared to a traditional TLS, it delivers reliable results suitable for various industrial applications.

These findings highlight the effectiveness of the Elios 3 in capturing high-quality 3D data, even in challenging environments. Whether for inspection, mapping, or asset management, the system proves to be a valuable tool in the field of 3D mapping.

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