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.
What makes GeoSLAM referencing different?
More accurate: GeoSLAM scanners are used with known control points and survey grade pins, rather than more traditional moveable targets. This reduces the margin of error within point clouds.
Save time: using known survey control points means there is no need to manually position individual targets before every scan. Data capture can then be repeated regularly, faster, easier and with no concerns that reference points are captured in different places each time.
Safer: in dangerous or inaccessible areas, targets are not required to be physically positioned on pre-defined control points prior to each scan. This reduces the time exposed to hazards and unsafe areas.
Industries using control points
Geospatial
Easily reference point clouds and produce reports highlighting accuracy values.
Mining
Regularly monitor site operations (e.g. stockpiles) and hazards.
Construction
Compare changes over time and map progress onto predetermined CAD/BIM models.
Using control points with GeoSLAM
Capture
All GeoSLAM ZEB systems are able to capture reference points using the reference plate accessory. These reference points can simply be measured by remaining stationary for periods during a scan and will be recognised during the processing stage. Points can be captured from a horizontal or vertical position, depending on which ZEB system is used, making it easier than ever to georeference datasets.
Process
Using the Stop & Go Georeferencing workflow in GeoSLAM Connect, datasets can be automatically referenced through a rigid or non-rigid transformation.
Rigid Transformation
Scans are rotated and adjusted and reference points are matched to the known control points without changing the scale factor. A single transform is applied to every data point in the point cloud.
Non-Rigid Transformation
The scale factor of datasets is altered to suit the control points – every data point is moved to a new position; this means the relative positions of these points also changes. This method is better suited for poor SLAMenvironments.
A clean georeferenced point cloud is produced using both methods. An accuracy report of the transformation is also generated and includes an RMS error value.
Point clouds with endless possibilities
Once georeferenced using control points, point clouds can be optimised further using leading third party software:
Comparisons with existing CAD/BIM models
Point cloud to point cloud registration showing changes over time within a given area
CAD/BIM model creation
For more information about our third party partnerships, head to our integrations page.
Case Study
Mapping hazardous mines under intense time constraints
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
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.
1. What is a point cloud? What measurements are included in a point cloud?
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 scanning is the process of using a 3D laser scanner to capture different points, measuring an area. You can quickly generate a point cloud with mobile mapping devices to capture dimensions, size and layout data.
What is Point Cloud Data?
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.
What is Point Cloud Processing?
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.
2. How do you create a point cloud?
Firstly, scan your object with an easy-to-use 3D laser scanner such as a ZEB Revo RT. When creating 3D point clouds, you might find that some objects need multiple scans from different viewpoints which are then merged in the software later. This is because a three-dimensional scanner can only record data points for the surface within the scanner’s line of sight and the object may need to be passed twice to capture the entirety of its geometry and reduce occlusions (gaps in data).
Next, remove the USB memory stick and plug it into your computer. A 3D scanning software, such as GeoSLAM Connect, will render the points from the raw data in real-time to give you a complete point cloud to represent your object in 3D space.
LiDAR vs Photogrammetry
There are two different methods of creating a point cloud, LiDAR and photogrammetry. Whilst either of these systems do the job, LiDAR laser scanning has an increased accuracy.
3. How long does it take to create a point cloud?
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.
4. Do you need to be trained in point cloud software to create a point cloud?
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.
GeoSLAM Connect – point cloud measurement
Point cloud data collected using the ZEB Horizon mounted to a UAV
5. What is the perspective on a point cloud?
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.
6. Can a point cloud be created in colour – how?
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. When using a GeoSLAM ZEB Horizon, colourised point clouds can be created by using the ZEB Vision accessory and workflow within the GeoSLAM Connect software. Learn more about how to colourise a point cloud here.
GeoSLAM point cloud animation of a warehouse facility in the UK
7. How do you put multiple point clouds together?
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.
stop-and-go alignment feature in GeoSLAM Connect
8. What are the best point cloud formats to use?
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.
9. What is a point cloud used for?
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.
Scanning a cavity with the ZEB Horizon
Location
Hattorf/Wintershall Facility, Germany
Scanned
Cavity
Size
70m Deep
Scan time
N/A
Industry
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.
Measurement Procedure
01
Preparation of the survey: mounting of the scanner on the cradle and mounting of the rope system for lowering and raising the scanner
02
Starting the measurement at the upper end of the opening to the cavity
03
Lowering of the scanner, 50m deep, while the ZEB Horizon captures data
04
Raising the scanner, 50m high, while the ZEB Horizon captures data
05
Finishing the scanning process at the upper end of the opening to the cavity
06
Ascent from the mine and analysis of the scan data in the office
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.
Embracing Digital Technology in Construction
Why firms need to double down
Getting the full value of digital in construction – why it’s so hard.
Innovation in construction gets a bad rap. Which feels somewhat unfair, after all, it is a ‘bricks and mortar’ industry, heavily reliant on equipment, machinery and a ‘hands-on’ workforce. The industry is often flouted as falling behind others in how it has embraced technology. Yet in recent years in particular, many forward-looking construction companies have deployed innovative solutions to better, and more safely, construct buildings.
But few companies have captured the full benefit of digital, and some have questioned whether they have the right approach. Piloting is one-thing, getting company-wide adoption is another. And it’s not hard to see why. As construction projects are typically fragmented, there are a number of hurdles for companies to overcome:
Data, Data Everywhere
Making good decisions relies on insightful data, and construction sites have a lot of it. In fact, the volume is simply staggering. However, it exists in siloed, distributed forms. There isn’t a single source of the truth.
Complex Supply-Chain
The success of a new build relies entirely on the strength of the team, more specifically the flow of data between all parties. With multiple layers of contractors and subcontractors in the project delivery supply-chain and with constant moving parts, tight collaborations is essential. But many firms struggle to operate a common data exchange.
Stuck in Analog
The construction process remains one of the least digitised industries worldwide. Many processes are still manual, error-prone and have a not-so-hidden penalty cost (there’s a 3 in 4 chance the scheduled completion date will delay by 40% or more on mega projects). Disputes, claims, fines – the risks of delays and cost overruns are a reality for many construction firms who have failed to automate.
Digital Isolation
As projects vary greatly, it’s hard to develop tools and methods that can be applied repeatedly. Teams or business units may develop their own subscale solution, without co-ordinating with others. Despite an influx of new technology providers to the sector, many of them offer stand-alone solutions that are not integrated within the wider use of technology in construction companies.
With the global population predicted to hit 9 billion by 2050 – and two out of every three people living in cities by 2050 – the demand for better, faster greener construction has never been greater. In addition, due to the pandemic, there is increased pressure on the construction sector to help ‘level-up’ the economy. Innovation and pace are needed. Could digital technologies, well-chosen and well-deployed, provide the key?
BIM is the right direction, but isn’t the whole answer.
According to the Future of Construction, Building Information Modelling (BIM) is the centre piece of the construction industry’s digital transformation. Over the last decade BIM awareness and adoption has grown from little more than 10% in 2011 to over 70% in 2020. And the benefits speak for themselves: NBS reports that adopters report greater predictability of building performance, price and programme; as well as reduced risk and increased profitability.
Yet while BIM standards are becoming embedded, and thankfully fewer people see BIM simply as ‘3D modelling’, there is still work to narrow the gulf between ‘BIM engaged’ and ‘BIM laggards’. Deploying cutting-edge technology is only one aspect. Having the mindset and approach to collaborate is what will really unlock the value of the tech.
At the core of BIM success is collaboration. In fact, you can’t really ‘do’ BIM if you don’t have the entire team on board in the earliest stages. NBS
Paving the way to success: why you need a holistic approach.
Aside from BIM, there are a number of connected construction technologies that are being adopted to streamline and ease the process of constructing our built world. But given the array of new technologies on offer, where’s the best place to start?
When the pandemic hit in 2020, and ‘working from home’ just became ‘working’, we all realised the difficulties in communicating and collaborating with remote teams. Add to that the challenge construction professionals already had of multi-layered teams, and it’s easy to see where the friction could be.
What makes construction complex is not the complexity of the building, it’s the number of people that are required to work together to make it happen. Nathan Wood, Executive Director, Construction Progress Coalition
While it’s tempting to cherry-pick solutions that fix a particular problem, developing narrow use cases may mean missing out on the wider opportunity. But by taking a collaboration-first approach and starting with technology that improves knowledge-sharing, smooths interactions and boosts interoperability, this could have significant knock-on effects to address other challenges, too.
For example, selecting tech that has the potential to integrate well with all other platforms means you’re not facing digital isolation. And by putting data transparency and data collection first by choosing tools that create 3D maps, this data can in turn, be used as the anchor for better decisions between all parties. And in unlocking collaboration barriers, this could be the key to creating lasting value.
In ‘Decoding Digital Transformation in Construction’ McKinsey & Co., cites how one collaboration tool drove down rework costs for a leading contractor. The quoted example talks about the contractor’s process for collecting comments on defects found onsite. Workers typically provided anecdotal, unstructured or difficult to act on feedback, which resulted in unplanned rework and delays.
This radically turned around when the contractor introduced a digital app to tag defects against specific elements in the BIM model and store them in a common data environment. A simple but effective collaboration solution that on-site teams could easily adopt. It smoothed out communication plus reduced rework and improved the bottom line.
5 ways a collaboration-first approach can transform Construction
Companies that take a collaboration-first approach put themselves in a much stronger competitive position. Not only can they get first-mover advantage, but they can boost productivity at the same time as keeping costs down:
Save Money
Construction has a long record of poor productivity and firms experience delays on a quarter of their projects, with nearly one fifth of projects going over budget. But with the wide adoption of mass data collection technologies, site workers can now carry out a weekly, or even daily, ‘as-built’ scan of a site which highlights any discrepancies or defects during the build. NBS research suggests that 3D modelling technology can deliver cost efficiencies (60%) and increase speed of delivery (55%).
Unify Delivery Teams
With multiple stakeholders engaged at various points of the project lifecycle, having “one source of the truth” such as BIM, enables greater collaboration and more informed decision-making. Data is brought out of silos and there’s a consolidated view of all critical information, that everyone can see, in real-time. This improves workflow, predictability and removes bottlenecks. Critical to this is having a mapping tool that accurately captures the data in 3D model form and provides an anchor for all data extracts.
Automate Construction
AI-powered solutions not only automate but accelerate non-value-add tasks across teams. This helps improve site efficiency and allows site workers to expand their capabilities. For example, on site, AI can provide real-time alerts in the event of safety violations, such as if PPE is not used at all times. And in the back office AI can easily reconcile budgets and billing by matching what happens on the ground to what’s been billed.
Improve Data Integrity
To be able to make better decisions faster, construction professionals need to know they’re confidently working with the most accurate data. A Common Data Exchange, such as the one being trailblazed by the Construction Progress Coalition will not only transform project collaboration but address the common data dilemma of getting the right info to the right people at the right time. It will also improve overall data integrity, data usage and make it easier to evidence compliance.
Perfect the Model Virtually
Being able to create an exact mirror of the asset in a digital twin, means you can spot and correct irregularities before building work starts, as well as monitor and correct defects on-site. This enables clients to mitigate some of the risk, time and cost impacts of complex construction projects. IDC predicts that companies that invest in digital twin technology improve cycle times of critical processes by 30%.
We make it, before we make it
Royal BAM Group has a phrase that has become synonymous with the company which is, ‘We make it before we make it’. This digital-first approach enables the company to easily visualise the construction schedule, flag any potential problems and get back on track – while saving on rework.
This type of approach which aims to manage and share data between all key parties, is especially helpful when regenerating buildings or constructing new builds in busy cities. Aside from operating on constrained sites in busy locations (e.g., where the site footprint is the building footprint), sites are often live environments, with businesses in occupation. Staging construction offsite, or ‘just-in-time’ construction enables all stakeholders to virtually test the stress factors and tolerances of an asset in multiple ways, before the asset is built.
How a leading UK contractor uses collaborative mapping technology to keep complex projects on track with daily scans
Wilmott Dixon is a privately-owned construction and interior fit-out specialist renowned for working on large and complex projects across the UK. To keep projects on-track, the contractor wanted to equip on-site teams with user-friendly mapping technology that could be quickly adopted and used by anyone. Scanners needed to be mobile, lightweight, and fast – and work in any weather. Mapping software needed to be automated, accurate and easy to interpret. GeoSLAM’s Construction Progress solution ticked all the boxes.
This innovative solution combines hardware, advanced SLAM and automated analytics for smart progress tracking. Site workers ‘walk-and-scan’ with a handheld SLAM scanner, and by simply plugging the scanner into a computer, the data is automatically processed using GeoSLAM’s smart data platform, Connect. This is digitally compared against the 3D model on record, and within minutes an automated report will show you the percentage of work complete/incomplete and a simple visualisation of the site, highlighting 3D changes.
The data is centrally stored providing a clear and reliable audit trail and remote teams can confidently share progress updates knowing they have a central source of the truth. Teams can continuously collect data as often as they need to, in some cases several times a day. The automated solution not only saves time and money but enables Wilmott Dixon to be on the front foot and proactively address any issues. It’s just one way the national contractor delivers lasting value.
The key unlocking value in construction
Like many industries, the future of construction is firmly rooted in leveraging the benefits of digital technology to deliver better outcomes. While building sites will always be an organised chaos of physical, tangible assets, there’s still a huge opportunity for technology to transform the way buildings are constructed. But if you’re not getting the full value from digital technology alone, don’t give up. There is a better way. Given the history of fragmentation and siloed working in construction, it follows that any, and every, digital innovation should seek to address this traditional way of working. And in doing so, will not only be a single-use case, but will have ripple effects across the whole value chain. Now really is the time to double down on digital efforts, collaboratively, of course.
References
Reinventing construction through a productivity revolution | McKinsey
McKinsey Global Institute: Reinventing Construction – A Route to Higher Productivity
Top 4 Challenges Facing the Construction Industry – Future of Construction
An Action Plan to Accelerate Building Information Modelling (BIM) Adoption – Future of Construction
NBS’ 10th National BIM Report | NBS (thenbs.com)
Decoding digital transformation in construction | McKinsey
Smart Market Report – Mitigation of Risk in Construction
NBS – National BIM Report 2019
Innovation Enterprise: Guide to Digital Twin Technology
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Blacklight, based in Romania, focuses on information technology that captures, measures and visualises data used in various fields of activity through providing valuable solutions.
Cybernetech Corporation, based in Japan, is a specialised trading company that offer advanced information and communication equipment and geospatial information technology.
Seiler Instrument is an American company that specialises in distributing surveying software and instruments serving industries such as surveying, engineering and construction.
Favre, Développement & Foresterie, based in Switzerland, are experts in geomatics and work with public and private landowners for forest management and environmental heritage.
3DT Digital Manufacturing is an Australian company that use the latest technology to adapt to changes in real time. It aims to help their customers become more efficient and productive.
Sigma Mascot, based in Hong Kong, provides solutions for 3D Laser Scanning, Geospatial systems and BIM services for industries such as Forestry, Construction and Real Estate.
Precision Laser & Instrument is an American company that offers comprehensive positioning solutions for the Construction, Survey, and GIS industries. They ensure high returns on investments and business success.
Export your point cloud into a range of formats, including LAZ, LAS, PLY and TXT. Datasets can also be exported as structured or unstructured E57 files, both of which include embedded panoramic images.
Surface normals at each point can now be computed from PLY and E57 formats, allowing users to export colourised data and create a high-quality polygonal mesh in third party software .
Stop and Go Georeferencing
Known control points are captured during a scan and automatically compared and matched to the associated coordinates during the processing stage in Connect. A rigid and/or a non-rigid adjustment can be made to the dataset and an accuracy report is exported, highlighting how successful the transformation was. Users can now view and manipulate the processing parameters to ensure a more accurate match between points.
Manual Alignment
Align multiple scans using a combination of manual and automatic processes. This workflow can be performed on two or more scans in the same project. Users have a choice to export the aligned scans separately or as a single merged point cloud.
JP Interactive Viewer
Leverage your GeoSLAM data by integrating JP Interactive Viewer into your workflows. JPIV allows you to unlock the full potential of your reality capture data and distribute actionable insights across your teams.
Our support team will be available for GeoSLAM Care customers on:
Monday 26th, 8 am – 4 pm (GMT)
Tuesday 27th, 8 am – 4 pm (GMT)
Wednesday 28th – 31st December – standard support hours
Monday 2nd January, 8 am – 4 pm (GMT)
From Tuesday 3rd January – standard support hours resume
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Autodesk Recap
Autodesk Recap contains tools for the manipulation and interpretation of high quality point cloud data and to aid designers and engineers in their creation of 3D models for real-world projects and assets (e.g. buildings and other infrastructure). It’s integrated design features help to streamline workflows, for example Scan to BIM. Recap is used to create initial design projects that users can then take into other Autodesk modules (e.g. Revit, Navisworks, AutoCAD).
Autodesk Navisworks
Autodesk Navisworks is a comprehensive project review solution that supports co-ordination, analysis and communication of design intent and constructability. The software can be used as a common data environment (CDM) for multidisciplinary design data created in a broad range of Building Information Modelling (BIM) packages. Using the tools within Navisworks, users can anticipate and minimise and potential problems between the physical building and the structural model.
Autodesk Revit
Autodesk Revit is a building information modelling (BIM) software. It contains tools which allows for planning and tracking throughout the building’s lifecycle. The software also allows multiple disciplines to collaborate more efficiently and make more informed decisions early in the design process. As GeoSLAM’s hardware allows for quick data capture, the equipment can be used to scan any existing buildings with the purpose of using the data to produce a digital twin.
Orbit GT allows users to capture and manage available 3D data (LiDAR data and imagery), extract a range of features for map production and make data sharable. All Orbit modules are ready to be used with 3D data from indoor, oblique, UAS and mobile mapping projects with other extensions that can be added to the Publisher and Orbit Cloud. Orbit can be used with the ZEB Discovery solution.
ContextCapture
ContextCapture is a reality modelling tool, allowing for the import of any point cloud and imagery data for the creation of high resolution reality meshes. These realistic meshes are accurate representation in 3D with high resolution RGB values of any scanned environment. By using GeoSLAM data in ContextCapture the users are able to create indoor reality meshes, which has been never possible before.
Microstation
Microstation is a 2D/3D software for designing building and infrastructure projects. It includes building information modelling (BIM) tools to document and assess any type of asset throughout its lifecycle. GeoSLAM solutions are often used in Microstation in the underground mining sector and to assess the current stage of any built environment, update the design model, and generate BIM information.
Deswik
With the GeoSLAM Connect stop-and-go georeferencing feature, users can easily georeference headings from known positions and map for analysis of overbreak, underbreak, undercutting and blast roughness calculations. This information is used within Deswik Mapping to analyse headings and levels.
Esri
Outputs from GeoSLAM’s solutions can be input to Esri’s GIS programs and apps, including ArcPro, ArcDesktop, ArcGIS Online and ArcScene. Join point clouds with local geodata or classify and edit scans based on their geography and statistics.
Micromine is a detailed and diverse mining software that provides solutions including modelling, estimation, design, optimisation and scheduling. Once data is exported from Connect it can be imported into Micromine and easily converted into wireframes. These can be used in Micromine for further studies into volumetric slicing, over and underbreak analysis, geologic modelling, face mapping and many more.
Terrasolid provides tools for data processing of airborne and mobile mapping LiDAR data and imagery. It includes different modules for tasks like data manipulation, calibration, georeferencing, point cloud classification, modelling and many more. It is a very powerful tool for a variety of industries, surveyors, civil engineers, planners, designers. Full, UAV or lite versions of Terrasolid modules are available for both MicroStation or Spatix software. All GeoSLAM products are compatible with Terrasolid and GeoSLAM data can be enhanced and edited with this software.
Floorplanner
Floorplanner allows you to draw accurate 2D floorplans within minutes and decorate with over 150,000 items from kitchen appliances to tables and chairs. Data is exported from GeoSLAM Connect in PNG file format with a scale of 1cm per 1 pixel and can be taken into Floorplanner.
Unity
GeoSLAM 3D point cloud data can be imported into Unity 3D Game Engine to generate interactive 3D scenes, where users can create 3D BIM models with textures and explore the space in 3D photorealistic environments.
Unreal Engine
Although Unreal Engine is mainly built for developing games, increasingly users are starting to use it to develop VR applications for understanding the current conditions of buildings, infrastructure and similar. Unreal Engine with a point cloud plugin can be used to visualise GeoSLAM point clouds in VR, which allows for collaboration, simulation and the understanding of current conditions of any scanned environment. Additionally, Unreal Engine tools are completely free.
Veesus Arena4D
Arena4D is a software package for marking up, annotating and editing 3D point cloud data containing a various export capabilities. It has a powerful and simple to use animation package which allows users to visualise massive point clouds in a simple way. GeoSLAM data can be simply uploaded and used in this package for the assessment of the current conditions of any structure, comparing differences between captured data (as built) to designed model (as designed).
Pointfuse
Pointfuse generates 3D meshes from point cloud data and classifies them to building ceilings, walls, windows and other features in IFC format. By using GeoSLAM data with Pointfuse users can very quickly create a classified BIM model with minimal manual input or expertise needed.
MineRP
MineRP has a Spatial DB that uses GeoSLAM data to represent visually the real environment of the underground mine. The software uses other data layers to overlay information on the digital landscape for decision making and tracking.
Pointerra
Pointerra provides a powerful cloud based solution for managing, visualising, working in, analysing, using and sharing massive 3D point clouds and datasets. Pointerra allows users to simply visualise and interrogate GeoSLAM data from anywhere.
Nubigon
Nubigon is a software solution that allows users to seamlessly interact with large point clouds and create visualisations and animations. Take your GeoSLAM point cloud data into Nubigon to create eye-catching flythrough videos.
Here is an example of a visualisation created in Nubigon using GeoSLAM point cloud data:
SLAM Environmental Pre-sets
Common data capture scenarios, such as UAV, outdoor, indoor, linear, and vehicle, have been characterised in Connect and data processing pre-sets for each environment have been defined. These can be selected at the beginning of the data processing stage allowing this process to be highly simplified.
Closed and Open Loop Georeferencing
Both methods match the scan data from a ZEB Locate system with the GPS data collected from the antenna to georeference the point cloud. When a scan starts and ends in the same place, this is classed as “closed loop”. “Open loop” is when the start and end position of a scan are in different locations. Standard SLAM practices apply to both methods of data collection.
Open Loop SLAM for the ZEB Locate is available on request – let’s talk about it.
Stop and Go Alignment
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.
Floor Slices
Horizontal and vertical slices can be taken from any location within the point cloud. Horizontal floor slices can also be automatically taken at a given height above the floor as defined in the processing stage.
Change Detection
Mostly used in the construction industry, multiple point clouds can be compared and any areas that have changed are automatically highlighted. Point clouds can also be compared with CAD models – for instance to track progress on a construction site – and PDF reports can be generated to present this information.
Queued Processing
Import multiple .geoslam files into Connect for processing and the scans will be processed in the order they were imported. The size of the queue can be defined by the user.
Enquire about the ZEB Horizon RT
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If your internet connection allows, move the Point Budget slider to the maximum amount available to view all the points in the cloud.
Making the point size smaller using the Point Size slider makes the data easier to view and interpret.
In the tools section of the viewer, you can measure the distance and angles of features within the pointcloud.
Using the materials section of the viewer, you can use the Select Attributes dropdown to view by intensity, elevation and RGB (if pointcloud is coloured)
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Coupling with hardware
Some SLAM software algorithms have been made available as open-source on the internet, but they are purely algorithms and not a product that you can take and use off-the-shelf. SLAM is most successful when it is tightly coupled and designed with specific hardware in mind. A generic SLAM cannot perform as well as one that has been specifically designed for a purpose.
Usage in multi-environments
Visual SLAM is closer to the way humans navigate the world, which is why it’s popular with robotic navigation. But in the same vein, vSLAM will have the same image-capture challenges as humans do, for example not being able to look into direct sunlight, or not having enough contrast between the objects picked up in the image. These can be overcome indoors, however, you may need to map a forest, tunnel or urban canyon. While SLAM technologies don’t rely on remote data (meaning you can scan areas where there is no GPS), you do need to ensure the SLAM technology you chose operate well inside, outside, in daylight and darkness.
Real-time data capture
Mapping a property is time-critical. Ideally, you want to make a single visit and gather sufficient data to create a highly accurate 3D model. Ensure the software you choose transforms 3D point cloud data into actionable information in real-time. This allows you to view and interrogate your data whilst still in the field, and make any adjustments, or collect missed data, then and there.
Flexibility and deployment
If you’re trying to map an enclosed environment (e.g. tunnel, mine) or a complex, difficult-to-access space such as a heritage building with tight stairwells and uneven floors, you need to use fully-mobile, adaptable technology. Wheel-based systems, often used with the vSLAM camera, will struggle with access. Handheld devices or LiDAR scanners that can be attached to a drone or pole and still deliver accurate results in a rugged environment are best for navigating hazardous spaces.
Speed and accuracy
While vSLAM is able to provide a qualitative high-level map and sense of the surrounding features, if you’re needing survey-quality accuracy and rich-feature tracking at a local level, you’ll need to consider LiDAR. Cameras require a high-frame-rate and high processing to reconcile data sources and a potential error in visual SLAM is reprojection error, which is the difference between the perceived location of each setpoint
and the actual setpoint.
Quality and distortion
In order to deliver the depth required for high-quality data, a number of depth-sensing cameras are needed with a strong field of view. In most cases, this isn’t possible, especially as cameras with high processing capabilities typically require larger batteries which weigh down airborne scanners, or limit the time of flight. LiDAR is both faster and more accurate than vSLAM, and can deliver detailed point clouds without expensive (and timely) camera processing.
