Applications of point cloud alignment

Do you need to align or overlap two point clouds for analysis and studies or simply to merge multiple surveys into a single file?

The solution is simple, and the operation to be carried out is known as point cloud alignment. Let’s see what it is and how to proceed following two possible alternatives, depending on the purpose of the operation and the tools available.

Key aspects of point cloud alignment

Definition

The alignment of the point cloud (point cloud alignment), or registration of the point set, is the process of accurately overlapping two or more sets of three-dimensional points in a common coordinate space. This process involves determining an optimal geometric transformation, which may include translation, rotation, and scaling, to minimize the difference between corresponding points in the different sets. The main goal of point cloud alignment is to integrate data from different sources or perspectives, creating a coherent and uniform model used in applications such as construction surveying, robotics, medical imaging, augmented reality, and 3D reconstruction. In the construction sector, point cloud alignment is especially necessary when there is a need to merge multiple point clouds obtained from different survey campaigns to create a complete virtual model, useful for various purposes and for comparing the same scenario at different time points (stages of a construction site progress, damage survey in case of calamitous events, etc.).

Once the alignment of the point clouds is obtained, it is possible to proceed by transforming the digital survey into a BIM model.

Aligning the point cloud initially involves finding a spatial transformation (e.g., resizing, rotation, and translation in different planes) that aligns two point clouds. The goal is to minimize the difference between the two or more sets of points that make up the cloud. The transformation can be rigid (involving only rotation and translation) or non-rigid (involving more complex transformations such as resizing).

Point cloud visualization in Edificius

Applications

Point cloud alignment finds applications in various sectors, thanks to its ability to combine data from multiple sources into a coherent and accurate model. Below are some of the main applications.

• Autonomous driving
  • LIDAR scans alignment: autonomous vehicles use LIDAR scanners to collect data on the surrounding environment. Point cloud alignment allows for the creation of accurate 3D maps that help the vehicle navigate safely, identifying roads, obstacles, and traffic signs.
  • Sensor fusion: By combining data from different types of sensors (LIDAR, radar, cameras), it is possible to improve the understanding of the environment and the accuracy of the autonomous driving system’s decisions.

• Medical imaging
  • Scan merging: In radiology and other medical disciplines, different scans (such as CT, MRI) can be aligned to create a complete 3D model of the body or a specific organ, facilitating diagnosis and surgical planning.
  • Tracking changes over time: By aligning scans taken at different times, it is possible to monitor the progression of a disease or evaluate the effectiveness of a treatment.
• Robotics
  • Object recognition and localization: Robots use point cloud alignment to recognize and locate objects in dynamic environments. This is essential for activities such as object manipulation, autonomous navigation, and interaction with the environment.
  • Mapping and SLAM: Alignment is a key component of Simultaneous Localization and Mapping (SLAM), a process that allows robots to build maps of the environment while determining their position within it.
• Augmented reality
  • Alignment of virtual objects: To create immersive experiences, virtual objects must be accurately aligned with real objects in the user’s environment. This allows for overlaying virtual information on real surfaces, enhancing the interactivity and usefulness of AR applications.
  • Human-machine interaction: Improving the accuracy of virtual objects compared to the real world allows for a more natural and intuitive interaction, crucial for training, maintenance, and remote assistance applications.
• 3D reconstruction
  • Creation of accurate models: Aligning point clouds from different viewpoints or from successive scans allows for the construction of detailed and accurate 3D models. These models are used in architecture, engineering, manufacturing, and forensic analysis.
  • Restoration and preservation: In cultural heritage preservation, 3D scans of artifacts and structures can be aligned to create precise digital copies used for studies, virtual restoration, and reproductions.
• Manufacturing industry
  • Quality control: Point cloud alignment can be used to compare 3D scans of finished products with the original 3D models, identifying defects and ensuring that products meet specifications.
  • Rapid prototyping: Combining data from different stages of the production process allows for verifying the accuracy of prototypes and making necessary changes quickly.
• Architecture and construction
  • Construction site monitoring: Construction site scans can be aligned over time to monitor progress and ensure compliance with approved plans and projects.
  • As-built documentation: Creating accurate 3D models of existing buildings and those under construction (thanks to the as-built survey) for documentation, asset management, and work planning.

Point cloud alignment is a versatile technology that, by integrating data from multiple sources, enhances accuracy and effectiveness in a wide range of applications, revolutionizing sectors such as autonomous driving, medical imaging, robotics, and many others.

How to align two or more point clouds

If your goal is to start from the survey carried out with one or more point clouds to build the BIM 3D model (scan to BIM process), you can use a BIM architectural design software that allows you to view the point clouds and align them with each other before proceeding, in the same environment, to create the complete virtual model.

In this case, it is necessary to upload the point clouds to the cloud and import them into Edificius. The alignment will take place manually by moving the model snap handle to a known point common to both point clouds. The handle also allows for translating and rotating the model according to the X, Y, Z planes.

If, instead, you only need to view the aligned point clouds to analyze changes over time or compare data sets, you can use a cloud application for point cloud federation.

BIM models federation with usBIM.federation

Even in this case, it is necessary to upload the point clouds to the cloud in order to create a new file for the federation. At this point, the alignment between the point clouds (or between BIM 3D models of different formats) is done easily, using commands that allow the following operations:

• translation (X,Y,Z);
• rotation (X,Y,Z);
• scaling factor.

By varying these parameters, it is possible to manage point cloud alignment flexibly.