( read )

Future trends in laser scanner technology

By Charles Thomson

All indications are that, in the future, laser scanning will become more powerful, more useful, and more affordable — influencing a huge array of industries. Laser scanner technology will continue to advance in tandem with developments in computing capabilities, and follow the trajectory of many technologies to become cheaper and easier to use. 

What we will discuss here are the ways in which laser scanners have advanced recently, known areas of investment for the future, and the likely way in which the technology will change. Primarily used by surveyors, laser scanners and laser scan datasets have become increasingly vital to a growing number of industries. Not only will the technology change, but how it’s used and who benefits will continue to evolve.   

1. The expansion of LiDAR and growth of mobile LiDAR

LiDAR is a technology that is skyrocketing, changing the way we collect and refine topographic data. What makes LiDAR so effective is the capability to direct 3D measurements to collect information from objects and the ground beneath. LiDAR works by shooting powerful laser pulses towards the target and collecting the backscattering signal. These systems are the current mainstream and use a selection of spectral wavelengths to convey the data collection.

Unmanned aerial systems (UASs) are increasingly important as a scanning vehicle. Mapping and surveying drones provide an easy-to-deploy platform for aerial views of an area of interest. Currently, there are some factors limiting the use of drones regarding operation time and the development of regulations in many countries. At best, drones contribute to the production of valuable 3D and image data for needs in various engineering projects, urban planning and scientific tasks. Longer operational times for UAVs are being delivered by improved avionics and battery life.

GNSS-free laser scanning has also developed rapidly. Systems typically consist of low-cost laser scanners and inertial measurement units. It is very likely that we will see the spread of LiDAR data being used and augmented with visual odometry from cameras. The development is possible due to the miniaturisation of sensors and SLAM ( Simultaneous Localisation and Mapping), LiDAR odometry and mapping (LOAM) and related algorithms. SLAM enables accurate mapping where GNSS localisation is unavailable, such as indoor spaces. SLAM algorithms will use a combination of data streams including LiDAR and IMU data to simultaneously locate the sensor and generate a coherent map of its surroundings.

2. The spread of point clouds

Data produced by laser scanners is normally first stored as a ‘point cloud’ — a collection of spatial points each representing the scan measurements of a single laser pulse. Highly versatile, point clouds are ever more relevant in a wide range of application areas. Data availability, accuracy, density, and size of 3D point clouds are forecast to vastly increase within the next years. 

With advances in a number of technologies, point cloud data will be captured in an ever-increasing number of ways — ground-based, airborne and spaceborne platforms — from grain-scale to global overview. Different scales and viewpoints will provide comprehensive data for environmental analysis, assessment of natural resources, development of urban infrastructure, and critical services. 

Semantic point clouds, temporal coverage, multimodal data sources, and automated processing will form the framework for future scanning data. The increasing use of point clouds will see an explosion in the need to manage data — localised processing of data and direct field upload of point cloud data to cloud services will likely become the norm.

Download your free premium guide

3. The need for automation and speed

Mobile mapping systems will increase the ability to scan and map with incredible accuracy. With the ability to “collect everything”, how can surveyors manage all of that data? The key answer will be to minimise human intervention by automating processes.

Machine learning and AI are becoming increasingly integrated into scanning technology. There is a trade-off between pre-processing of data “at the edge” to reduce file sizes with the need to consolidate and upload scans to be part of an overall model — for example as used in Building Information Modelling (BIM).

In the area of terrestrial laser scanning, automated registration of scans is an interesting example of how automation might work. Point cloud processing incorporating machine learning algorithms and vector analysis can greatly increase the speed and diminish the need for manual involvement in scan alignment.  

Most existing registration solutions work by identifying features such as artificial targets, planes, or lines in each scan. Those objects are then used as references to align overlapping scans. However, “natural features” in a scanned environment can be used instead as “virtual” references. There can be millions of such natural features identified in a typical scan leading to faster alignment and better accuracy. Using a vector-based process, alignment time has already been reduced by as much as 40%-80%. Combined with automation, this is how larger and larger data sets can be processed more efficiently. 

4. The advent of multimodal scans

More and more, scanning, sensor and visual data will be combined to provide a complete picture. For example, UAV-based airborne sensors and mobile laser scanning can be combined with imagery bringing together the flexibility of mobile systems and allowing for short response times and low mobilisation costs. 

In this field, sensor technology is still experiencing a significant reduction in size and price. Simultaneously, the performance and accuracy has been improved to provide detailed 3D structural information on tunnels, roads, urban scenes and industrial sites. 

Other examples include vehicle-mounted kinematic mapping systems for road and street data for autonomous driving; backpack scanning for collecting 3D data from cultural heritage sites, buildings, streets and terrain. GNSS-IMU and SLAM-based laser scanning systems will be mounted on virtually any kind of platform in varying environments,

5. AR/VR integrating with laser scanning 

While Augmented Reality and Virtual Reality can be considered as an outcome of scanning technology, developments in this area will also drive the future of scanning technology

Apple is reportedly hoping to deliver a long-range 3D camera system in a future iPhone by 2020 at the earliest, according to Bloomberg. However, it wouldn't be possible with the dot projection scheme Apple relies upon for its existing TrueDepth camera technology. Instead, the company will likely turn to laser scanning. With a laser-aided, 3D depth mapping system, future iPhones would be able to scan entire rooms, and more accurately represent the position and proportions of computer-generated objects in the real world. 

6. Modelling the future

These are remarkable times for the intersection of data science and scanning technology in computer and robotic vision. Technology has matured to the point where it is viable to equip smartphones, robots, autonomous/connected vehicles, and other mobile devices and machines with an array of sensors. 

Developments in laser scanning and point cloud processing will provide significant impetus and cost savings via automation of mapping processed with improved output and quality of data. Combined with the rich datasets produced by sensors, devices and machines will perform a variety of impressive and challenging tasks. 

Multimodal LiDAR data will increasingly be used with aircraft, drones, vehicles, backpacks and handheld mapping systems all serving as a means to gather complementary data for virtually any task imaginable.

Dense point clouds with multispectral information will provide a common starting point for automated modelling workflows and direct visualisation applications providing a platform for many as yet unknown future applications.

Laser scanners will become better, small and more mobile 

The story of laser scanners is not too different from most evolving technologies — they are becoming better, cheaper and smaller. The real change is to the use cases. As any technology becomes more easily accessible, new ways to apply that technology become viable. 

The expansion of applications for laser scanners are already starting to be seen. Driven by smaller and cheaper scanners, armed with the aforementioned improvements to point cloud registration, land surveyors have become integral members of many engineering and construction projects. By providing scan data to inform the basis of 3D CAD models and enable quality assurance checks of prefabricated materials and project stages, efficiency and outcome improvements are delivered.  

The development of scanners like the Leica BLK360 (one of the smallest and lightest scanners on the market today) has delivered access to laser scanner technology to even the smallest businesses and survey professionals. What is clear is that laser scanners will continue to improve — it’s down to businesses to decide which doors this opens for real use-case changes. It’s an exciting time. 

Vercator-Free-Trial