Introduction to Control Points

What is a control point?

A control point is a surveyed fixed reference point used to establish the absolute position of a point, for example on a building site.

Note: A control point is fixed in place (usually by a surveyor) using a total station to record the exact coordinates of the control point. These coordinates are used to create a Control Point File which is used later when processing the dataset created whilst scanning.

• Control points can be fixed to the ground or to walls.

• Surveyors sometimes refer to control points as survey markers, survey targets or anchor points.

• Control points can be stickers, nails, or marked metal plates that are fixed in place.

Why use control points?

Control Points help to maintain accuracy of the dataset once it is captured by the Navvis device and later processed together with the control points. Control point address cumulative distortions, such as drift and tracking errors, that can occur, refer to Why does drift error occur?

Capturing control points while scanning with your NavVis device has the following benefits:

• Global or local data registration: Control points help ensure that the scanned dataset aligns accurately with the real-world coordinates.

• Enhanced Data Accuracy: Control points are important in minimizing discrepancies between scanned coordinates from the device and the surveyed coordinates from the total station. This process contributes to a more accurate point cloud.

• Cross Data Alignment: When multiple datasets are captured and processed, control points ensure that they are consistently aligned with each other, maintaining spatial accuracy across the entire project.

• Verification and Validation: Control points provide a reference for verifying the accuracy of the processed data.

• Enhanced SLAM Performance: The use of control points can improve the performance of the SLAM algorithm by providing fixed reference points, leading to more reliable mapping results.

Why Does Drift Error Occur?

Drift error is when the trajectory data generated by the SLAM algorithm diverges from the true path as you scan. It is caused by the accumulation of smaller errors, such as tracking errors, or positioning errors that arise from sensor noise.

Drift is rarely a problem in short scans but becomes more of an issue the longer you scan. It is easy to see in the data, for example, when a straight corridor looks bent or a stairway is twisted.

How to Reduce Drift using Control Points

Loop closures are still the most effective method of minimising drift and maintaining a stable SLAM and their importance should not be misunderstood. However, loop closures work well in large spaces such as gymnasiums, outdoor areas, or large offices, they can diminish in effectiveness in certain specific environments, such as in long corridors.

In a long corridor using control points is the most effective method for locking down accurate scan data. The process is straightforward:

1. Distribute control points throughout the scanning area.

2. Capture their coordinates using a total station.

3. As you scan the area, ensure the device captures these surveyed control points. For capturing a control point with:

   1. NavVis VLX refer here.

   2. NavVis MLX refer here.

The mobile mapping system will use all this information to accurately align the point cloud, reducing errors.

Below is an example illustrating how control points enhance the accuracy of scans when working in a corridor.

Place control points in the corridor.

The surveyed control points can be either in an arbitrary local coordinate system, or in one of the Global Geodetic survey systems (called Spatial Reference System in IVION).

Surveyed control points added to a dataset during post-processing function as small corrections to the device’s calculated trajectory. In conjunction with loop closures and the algorithms used in NavVis Processing the dataset can achieve an extremely high degree of accuracy.

The graphic is intentionally exaggerated to highlight the issue—compare the calculated trajectory to the actual coordinates of the control points.

Post-processing algorithms use control point data to correct drift and tracking errors within the datasets.

Furthermore, the algorithms extract alignment information. This data is derived from the positions of the control points and datasets, subsequently registering the dataset within the coordinate system of the control points.