Surveying buildings is difficult and accessing hard to reach areas, like dropped ceiling or raised floors, without disrupting business can be seemingly impossible. In this blog we’ll discuss how SLAM and LiDAR technology has made scanning behind dropped ceilings a simple process.
GeoSLAM partners with drone inspection specialists Flyability for the launch of their new drone, Elios 3.
Having recently introduced our new ZEB Vision panoramic camera, we are now launching the latest update to our software platform, Connect 2.1. Learn more about the ZEB Vision and Connect 2.1.
Surveying buildings is difficult and accessing hard to reach areas, like dropped ceiling or raised floors, without disrupting business can be seemingly impossible. In this blog we’ll discuss how SLAM and LiDAR technology has made scanning behind dropped ceilings a simple process.
Control points are points within a given area that have known coordinates. They are a key tool in the geospatial industry and can be utilised in a variety of ways, including georeferencing point clouds and aligning aerial images to terrestrial data. By using control points, surveyors are able to accurately map larger areas and position overlapping surveys of an area together. They can also be used in non-geospatial industries, such as construction and mining, to show clear temporal comparisons between multiple surveys of the same area. This method of georeferencing is also referred to as adjust to control.
Previously, checkerboards and spherical targets have been used as control markers – these items are captured in surveys and can be identified for georeferencing or aligning. The main drawback with these methods is that they rely heavily on human interpretation when processing, meaning that the processed datasets may be susceptible to an increased amount of error.
When capturing handheld surveys, GeoSLAM systems are able to collect reference points. These can then be matched with known control points to reference scans and increase the level of accuracy.
Easily reference point clouds and produce reports highlighting accuracy values.
Regularly monitor site operations (e.g. stockpiles) and hazards.
Compare changes over time and map progress onto predetermined CAD/BIM models.
Once georeferenced using control points, point clouds can be optimised further using leading third party software:
For more information about our third party partnerships, head to our integrations page.
Beck Engineering, an Australian mining engineering consultancy specialising in mining and rock mechanics analysis, needs to rapidly map mines under intense time constraints using versatile technology which is adaptable to any environment. GeoSLAM’s handheld mobile mapping solution was chosen as it is compact, portable and delivers a high level of accuracy. With GeoSLAM’s “go-anywhere” 3D technology in hand, Beck Engineering has been able to supply invaluable data regarding the direct effects of mining to better understand the implications of a deforming rock mass. Beck Engineering is now able to accurately measure the shape of an excavation or tunnel over time. As a result, tunnels are safer, better designed and more cost efficient.
We have continued to use GeoSLAM products as they have proven to be affordable, lightweight and sufficiently robust devices for their application underground. GeoSLAM continues to produce a high-quality device that is at the forefront of practical mobile laser scanning devices.
– Evan Jones, Senior Rock Mechanics Engineer at Beck
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With mobile mapping technology readily available, anyone can effortlessly map the environment around them, whether it’s a cave, 10 storey building or a construction site. For newcomers to surveying, this tech breakthrough removes the dependency on trained experts – but it does require the mapper to have a basic understanding of a point cloud. What is it, how is it created and how is it used? In our latest education article, we look at the top point cloud questions and provide all the information you need to get started.
Point clouds are now faster, easier and more accessible than ever before. If you’re interested in mapping but aren’t trained in point cloud software – this guide is for you.
A point cloud is essentially a huge collection of tiny individual points plotted in 3D space. It’s made up of a multitude of points captured using a 3D laser scanner. If you’re scanning a building, for example, each virtual point would represent a real point on the wall, window, stairway, metalwork or any surface the laser beam comes into contact with.
The scanner automatically combines the vertical and horizontal angles created by the laser beam to calculate a 3D X, Y, Z coordinate position for each point to produce a set of 3D coordinate measurements which often includes its colour value stored in RGB (more on that in question 6) and intensity. These details can then be transformed into a digital 3D model that gives you an accurate detailed picture of your object.
The denser the points, the more detailed the representation, which allows smaller features and texture details to be more clearly and precisely defined. So, if you were to zoom in on a point cloud of The Tower Bridge in London, you’d see tiny points creating the whole point cloud.
Point cloud data is the term used to refer to the data points collected for a given geographical area, terrain, building or space. A LiDAR point cloud dataset is created when an area is scanned using light detection and ranging.
Point cloud processing is a means of turning point cloud data into 3D models of the space in question. This data processing is made possible with processing software such as GeoSLAM Connect.
It all depends on how many scans are needed and what exactly needs scanning. Or whether you’re using traditional stationary scanning equipment or mobile laser scanning technology which would considerably reduce scanning time. For example, a 130-scan point cloud dataset (which is a lot of point cloud data) of an office building including all the individual rooms, corridors and service areas could take nearly 25 hours to process with a traditional, static laser scanner.
Those scans may have only taken a day to collect with a mobile scanner, but manual involvement in processing means that the registration of that point cloud dataset can take around 3 days to carry out, and potentially longer if manual correction is necessary. Smaller datasets can be processed in hours.
With a device like the ZEB Revo RT a slam point cloud is created in real-time and you can see the live visualisation progress with the attached tablet or phone. It requires no processing other than extracting data from the device, so you can have a full point cloud in a matter of minutes – depending on what’s being scanned.
GeoSLAM’s Connect software is specifically designed for ease-of-use. With minimum training on the software, you will be able to process raw point cloud data by directly transforming it into BIM (Building Information Modelling).
Its menu is easy to understand and the tools and functions let you navigate your way through the cloud easily and efficiently. With GeoSLAM Connect you can create clean, georeferenced point clouds automatically.
Since a point cloud is a fully 3D format, you can view it from any perspective, no matter what device was used to capture it. You can capture a point cloud on foot using a handheld 3D laser scanner such as a ZEB Horizon, and then view it from the top-down as if you’re seeing the scanned environment from a drone. In fact, you can view any part of the point cloud, including objects and rooms, from any angle as required.
When you look at a colourised point cloud of a room, you’re seeing both the dimensional measurements and the RGB value. This data is taken at each point the scanner measured. The effect is that users (both new and experienced) can understand quickly and easily what they’re looking at because the point cloud looks more like a 3D photograph. Cloud colour can simply be added via your chosen format.
Handheld 3D laser scanners are efficient enough that many spaces can be captured in a single scan. However, larger projects such as a large sports arena or campus may require more scans for complete coverage, which means you’ll have a number of point clouds that you’ll need to merge into one final point cloud for the whole asset. A variety of software applications enable you to do this. However, if you use a GeoSLAM laser scanner, it makes good sense to use GeoSLAM’s complimentary Connect software.
Within GeoSLAM Connect you have the stop-and-go alignment feature where common static points are captured during several scans meaning that these datasets can be automatically aligned. A single point cloud is then exported as if the data was captured in a single scan.
Different scanners produce raw data in multiple formats, and each piece of software has different exporting capabilities. Output formats are also determined by what data is required and who needs it. If you wanted to store the data away for a long period, you’ll probably be best storing the point cloud as an ASCII file. Other popular formats are LAS, PTS, PTX, XYZ and Fast Binary.
GeoSLAM data is compatible with software that works for you with universal file formats (LAZ/LAS/PLY/TXT/e57) and can be imported into many different third party software’s such as Deswick, Esri, Micromine and Floorplanner.
It’s a non-intrusive way to accurately measure object properties in 3D. For example, sites such as care homes, stadiums and museums don’t have to be shut down in order to be measured. The measurements are also far more detailed than anything traditional survey equipment can produce.
In the architecture industry, which uses As-Built models; point cloud software eliminates time-consuming and costly revisits to the site and allows an architect to visualise and convey new concepts. Point cloud has become the new standard for all design industries as it provides an instant virtual model to test ideas with. They are also used to create 3D CAD (computer-aided design) models for manufactured parts, for metrology and quality inspection, and for a multitude of visualisation, animation, rendering and mass customisation applications.
Here’s an example of the GeoSLAM ZEB Horizon data being used to create a BIM model for a large hotel using Revit.
We hope this gets you out of the blocks and you quickly become a point cloud enthusiast. Creating point clouds is both easy and simple – and anyone can do it.
Looking for some inspiration on taking your point cloud to new places, check this out. You can also visit the Point Cloud Library here.
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With the recent introduction and constant evolution of handheld SLAM (Simultaneous Localization and Mapping) scanning, mapping underground has become safer, quicker, more automated, highly repeatable, and more effective.
Hattorf/Wintershall
Facility, Germany
Cavity
70m Deep
N/A
Mining
Laserscanning Europe | German Dealer
GeoSLAMs German dealer, Laserscanning Europe, were recently tasked with scanning a 70m deep cavity in a mine 500m below the earths surface. Using the ZEB Horizon on a cradle, Laserscanning Europe were able to successfully and safely capture the data, and this is their account of the job.
Data captured by Laserscanning Europe
Scanning with the ZEB Horizon | Words by Laserscanning Europe
The object of measurement is located in the Hattorf/Wintershall mining facility of the company K+S Minerals and Agriculture GmbH. This is a cavity (underground, vertical conveyor system) about 500m below the earth’s surface with a depth of 70m.
The cavity no longer has the original storage volume due to material deposits from years of operation. The environment is dusty and it is expected that material will be deposited within the conveyor system at any time. In addition, the cavity is not accessible to humans from any opening and access is only possible through 1m diameter openings.
The objective was to obtain a three-dimensional survey of the conveyor system with highest possible resolution for inspection of the systems condition. Furthermore, strict compliance with all work safety regulations, with minimal risk for the measuring team, was required.
For this job, a mobile laser scanner was used. Thanks to its specifications, the GeoSLAM ZEB Horizon is ideally suited for the special conditions underground. The scanner is also suitable for surveying a cavity that is only accessible from above through a narrow shaft.
The scanner was mounted on a cradle, which was modified to minimise rotational movements when lowered. A 50m rope was attached to the cradle, which was used to lower the measurement system into the cavity.
Furthermore, trained members of the mine rescue team were on site to provide security and enable the scanner to be lowered and retrieved safely.
Workflow of the analysis
Following the survey, the scan data was processed using the GeoSLAM HUB software. The raw data, i.e. the processing of the point cloud from the data of the laser sensor and the IMU, is automated as much as possible. In the case that a scan was not automatically processed (e.g. because few geometric changes are found in the object space), the focus of the SLAM algorithm can be influenced by adjusting various parameters. Once the data has been run through GeoSLAM Hub, a complete point cloud of the cavity is available in .laz format. All other common point cloud formats can also be exported with little effort.
Since the scanner could only be lowered linearly on the rope, the earth deposits shadow smaller areas inside the cavity.
Results
The result of this scanning is impressive. This cavity, which is not accessible to humans, was successfully surveyed with the help of the GeoSLAM ZEB Horizon. The point cloud documents the dimensions of the cavity according to the requirements. Further missions with the GeoSLAM ZEB Horizon with similar objectives are already being planned and implemented.
As the adoption of SLAM rockets, and new applications for mobile data capture are discovered each day the value of SLAM is being proven across businesses of all shapes and sizes. GeoSLAM technology continues to break barriers and the ever-increasing profile of SLAM users grows each day.
