Watch this webinar to learn all about the new features of Connect 2.3.
Key takeaways:
Location: Saudi Arabia
ZEB Scanner: ZEB Horizon
Scan time: 15 minutes
This data was processed in GeoSLAM Connect and the volume of the stockpile was calculated (15,000 tons) in GeoSLAM Volumes.
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Last Updated on 3rd March 2023 Georeferencing takes centre stage for GeoSLAM’s… Read More »Georeferencing takes centre stage for GeoSLAMs latest software release
Hamburg, Germany
25 minutes per scan
163 apartments and 13 staircases
Apartment Building
Surveying
Danish-based digital modelling company, Eseebase, works to digitise building assets globally. They collect relevant, accurate data and information, with the aim to make the maintenance of buildings more effective. During the lifespan of the company, they’ve created digital assets for more than 9 million square meters of space and over 400,000 flats within the housing sector.
This case study will dive into a recent project, that required the need for fast and accurate data capture, using GeoSLAM handheld scanners.
SAGA, controlled by the State-City of Hamburg, is Germany’s 3rd largest housing company and has nearly 140,000 residential units. They required up-to-date information and measurements of a large apartment building. Upcoming renovations to the apartment block meant that the information needed to be accurate and returned in a timely manner.
SAGA tasked Eseebase to capture the data. The team’s goal was to create up-to-date CAD drawings and a 3D model (BIM) of the apartment block.
The residential building has 163 apartments and 13 staircases that span across 7 floors. Furthermore, residents currently live in the apartments, so speed and professionalism were a priority. To limit disruption, the team had a few hours per day to scan the building. As a result, a requirement for an accurate and time-efficient method of data capture was essential.
Eseebase opted to work with GeoSLAM technology, as they are familiar with the solutions and workflows. For this project, the team obtained a ZEB Horizon scanner. They also made use of the ZEB Vision camera claiming the bubble walk-through feature from the 360o panoramic images were a useful reference when modelling.
The ZEB Horizon’s walk and scan method was a simple way of capturing an environment without any difficult setups. It also was a less intrusive way of obtaining data, benefitting the residents in the apartment blocks.
Additionally, the laser scanner transitioned well between apartments to hallways and stairwells, as well as from indoors to outdoors. The ZEB Horizon’s ease of use meant training was minimal, and there was a reduction in time spent in the apartment block.
The ZEB Horizon’s speed of capture also allowed Eseebase to scan the building’s interior in under three days, carrying out 7-10 scans per day that lasted 25 minutes each.
With the interior captured, the team focused on the exterior of the building. A close-up walk around the building gathered the necessary data, and a wider loop helped to capture the roof. A large body of water surrounds one side of the building, therefore Eseebase had to get creative and scan from a small boat they hired. The mobility of the scanner overcame this problem, whereas other mapping solutions would struggle due to their cumbersome nature.
Essebase used GeoSLAM Connect to process the final point clouds and they automatically merged the 23 individual datasets into one large point cloud.
Autodesk ReCAP produced RCP files from the point cloud, which was then imported into Revit where the CAD Drawings and 3D model was created.
In just three weeks Eseebase had presented the final deliverables back to SAGA. The speed of capture the ZEB Horizon provided cut down the overall delivery time, and the mobility saw that the process didn’t largely affect the residents.
Eseebase found GeoSLAM’s technology so efficient and beneficial that they have recently acquired the ZEB Horizon RT. They plan to use it, with the ZEB Vision, for future projects in Germany following similar workflows.
Ernst Koppensteiner, Head of Data Registration and Quality Assurance at Essebase, says “Capturing a building of this size comes with its difficulties, especially when scanning multiple staircases and rooms over several floors. The ZEB Horizon allows us to easily capture the necessary data quickly and with no issues”.
The ZEB Horizon is the most versatile scanning device we have found when it comes to using one system for Outdoor scanning, Indoor scanning and scanning in very confined spaces like cellars and attics”
– Ernst Koppensteiner, Head of Data Registration and Quality Assurance, at Eseebase
In this blog, we are proud to share our renewed dealers, with some brief information on their work within specific industries and where they’re located.
Watch this webinar to learn all about the new features of Connect 2.2, as well as a first look at GeoSLAM data in online data viewers for easy sharing and collaboration.
Key takeaways:
How precise and accurate are the 3D models you can make with the Elios 3?
Watch this webinar to learn the results from recent testing we did with our partners, Flyability, to assess the accuracy and precision of 3D models made using LiDAR data collected by the Elios 3 and processed on GeoSLAM Connect.
In the webinar we went over the results of the testing and explain how to use GeoSLAM Connect to make survey-grade 3D models with the Elios 3.
In this Chartered Institution of Civil Engineering Surveyors article, Dr Neil Slatcher talks all things SLAM, answering questions such as ‘What’s the difference between SLAM and traditional laser scanning?’ and ‘What kind of SLAM types are there?’.
In this Chartered Institution of Civil Engineering Surveyors article, Dr Neil Slatcher talks all things SLAM, answering questions such as ‘What’s the difference between SLAM and traditional laser scanning?’ and ‘What kind of SLAM types are there?’.
With ever-increasing research and development in the technology, the advances in both scanning hardware and processing software are improving the detail, scale and use of point cloud data. One of these improvements is colourisation. Adding colour has plenty of benefits when viewing and analysing point cloud data.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
