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Miniature 3D LiDAR on Small UAV Platforms

Contributor: Håkan Larsson, Senior Research Engineer, Swedish Defense

Research Agency (FOI)

Presented by

© 2014 Diversified Business Communications

TABLE OF CONTENTS

Introduction ............................................................................................................................................ 1

Development of UAVs .......................................................................................................................... 1

How LiDAR technologies compare .................................................................................................. 2

Why take LiDAR measurements from UAVs? .............................................................................. 4

Integration of miniature LiDAR on small UAV platforms ....................................................... 5

LiDAR UAV applications ...................................................................................................................... 7

UAV Photogrammetry ........................................................................................................................ 10

Conclusion ............................................................................................................................................. 10

Biography ............................................................................................................................................... 11



1

INTRODUCTION Small unmanned aerial vehicle (UAV) technology has improved at a rapid pace in recent years,

especially in terms of navigation and control processors. Fast-moving, nimble UAVs can offer users

new views of urban or rural terrains. Whether UAVs are used for recreational flights from the

backyard, for new camera angles in documentaries, or even by the military – these small crafts go hand

in hand with the latest imaging technologies.

Håkan Larsson has spent several years at the Swedish Defense Research Agency investigating the use

of miniature 3D LiDAR technology on small UAV platforms. Based on his experiments, Larsson explains

how best to integrate the two technologies, as well has how the pairing of LiDAR technology with the

latest iterations of UAVs may benefit certain private business projects, military information gathering,

or search and rescue operations.

DEVELOPMENT OF UAVS UAVs have had an explosive technical development phase in recent years. Inertial navigation sensors

(INS) in particular have expanded possible parameters for LiDAR imaging and the propulsion of the

engines has become stronger.

On top of all this, the control processors, algorithms and radio traffic and control communications with

UAVs have also improved. However, while lithium polymer batteries are pretty useful and are light

compared to other batteries, better battery technology could lead to even longer flight times.



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Figure 1

At the same time, there has also been an explosive technical development in laser scanners since 2013.

Laser scanners have become lighter, more reliable, and more accurate while also improving the speed

of data collection, data storage and processing.

HOW LIDAR TECHNOLOGIES COMPARE So why use miniature LiDAR technology on UAVs? To answer this question, it may be best to take a

look at other LiDAR technologies and see what they have to offer. Terrestrial LiDAR scanning, airborne

laser scanning, and mobile laser scanning will all have advantages and disadvantages when compared

to laser scanning integrated with UAVs.



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Figure 2

Terrestrial LiDAR can deliver extreme density in point clouds, and good range accuracy. However, the

measurement method includes static measurements and can be very time consuming. Terrestrial

LiDAR may also have unfavorable angles for ground points.

LiDAR is ideal for airborne surveying. The strength of aerial LiDAR is that it covers huge areas very fast

– many square kilometers per flight. Airborne LiDAR also has the capability to penetrate down to the

ground. But there could be denser point clouds, and a bit better range accuracy from airborne LiDAR.

Figure 3



4

Mobile laser scanning is a different kind of dynamic infrastructure machine. Mobile laser scanning (on

a vehicle) can cover great distances. However, the point clouds can be uneven. Often the point clouds

produced will be very dense near the vehicle, but quickly become sparse farther away from the vehicle.

Mobile laser scanning also has unfavorable angles for ground points, especially in the case of deep

ditches or higher vegetation.

Figure 4

WHY TAKE LIDAR MEASUREMENTS FROM UAVS? Miniature LiDAR measurements from a UAV could be the missing link between these other LiDAR

technologies. The existing limitations from the LiDAR systems, once incorporated into a UAV, open up

to allow the user to acquire dense point clouds from low-flying heights, or from favorable angles. This

set-up allows the LiDAR scanner to reach inaccessible or dangerous angles that terrestrial or other

existing LiDAR systems cannot. And, of course, a UAV can't cover areas as expansive as the aerial

system, but it can cover several thousand meters at least. UAVs may be a superior choice for LiDAR

scanning projects that are smaller in area, up to a couple of thousand meters.



5

INTEGRATION OF MINIATURE LIDAR ON SMALL UAV PLATFORMS In addition to investigations for military use, the Swedish Defense Research Agency began integrating

UAV and LiDAR technologies with a future business product in mind. As of now, the project has

integrated a laser scanner with an external INS along with a pressurized altitude meter, a compass and

a GPS. All of this has a data link to the ground for data collection. In all, the UAV in this project weighed

7kg, with 1.3 kg of that from the scanner and 1.1 kg from the batteries.

This LiDAR scanner had 32 different lasers and detectors with a range of 1-70m. Its accuracy was 2cm

at a 25m range, and it shot 700,000 points per second at a wavelength of 905nm.

Very often, it's best to test reflectance and range independently in the laboratory. Normally,

manufacturers put their values to a certain limit that is actually the limit in the best circumstances.

However, in this project, the values proved to be much better in our independent tests.

Another key to integrating these two technologies is calibration, especially when working with 32

lasers.

Figure 5



6

We used scans taken close together in time, in this case two consecutive rotations of the scanner, to

perform astronomic calibration.

Figure 6

In this case, a ground model was used for the calibration. Without calibrating with scans taken so close

in time, there would have been a much larger error.

Regulations regarding UAVs will be an ongoing constraint and issue as UAV technology evolves. In the

case of this project, there were regulations and practical constraints of working in an area with a lot of

students and people walking around. For this project, the UAV was flown over vegetation, as well as

being mounted on a Land Rover. It took 3 minutes to go a distance of about 600m in one go.

Once the data was processed, it was clear how much data could be generated after performing

accurate calibration. The process data generated without prior calibration – using just INS, the

compass and the altitude meter – was not as rich. And certainly there was a need for further

backtracking to reduce even more revolutions that close. That work will start at the beginning of next

year.



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LIDAR UAV APPLICATIONS Search and rescue operations are just one type of urban scenario that could benefit from LiDAR-UAV

applications. UAVs can hover just outside second story windows, for instance. And the LiDAR is

capable of penetrating windows and imagining the situation within a building that may be inaccessible

to rescue personnel.

Figure 7

In the case study, the UAV passed a building at a rate of 6m/s, at about 30m away from the building. At

this speed and distance, the UAV certainly got a lot of points in the back of the office. From a closer

vantage point, there would be even more points generated in the building.

This technology may also be used to detect objects through vegetation. By comparing miniature LiDAR

on UAV scans to terrestrial scans, it's clear how much easier it is to penetrate vegetation.

Another application along these lines for the military is to detect changes in the earth. For instance,

now most modern militaries will have to contend with so-called improvised explosive devices, or IEDs.

IEDs are homemade bombs, and usually small in dimension, and buried under roads or commonly

traveled ground.



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Figure 8

Miniature LiDAR on UAVs can make use of automatic change detection algorithms to find threats

approaching through vegetation, and signs of small objects. As long as there was a free line of sight,

members of the project could detect one objects as small as one cubic decimeter.

Now, one weak point in setting up an IED under a road or path, is that it's hard to put the layer of soil

back in the same leveling. It's certainly possible to detect this disturbed soil with automatic detection

calculations from a liar-equipped UAV.

These penetration capabilities can also improve situation-awareness when mapping both urban

scenarios and terrain. It opens up the possibility for using UAVs and LiDAR for forensic measurements,

or to take details from other LiDAR systems, and combine those afterward for more insightful

capabilities.



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Figure 9

For example, take this tower that is 1km high. In this case, three targets – one in the field and two in

the forest – were measured with an optic scanner. Now, these targets can be detected automatically

with the right calculations. The first step was to estimate the ground with certain algorithms, and then

only consider the points from the ground level up to 3m above ground. Of course, the targets were

within those 3m. After that, the point cloud is again divided into voxels. The density is examined, and

how the image is clustered is also considered while stray points here and there are eliminated.

Figure 10



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UAV PHOTOGRAMMETRY Photogrammetry, when compared to miniature LiDAR on UAVS, has certain advantages. For example,

in urban environments, photogrammetry makes very handsome models. However, there are some

limitations and it takes a lot of manual work to get a finished model. Where photogrammetry is limited

in its ability to penetrate trees, LiDAR can penetrate through vegetation and even windows.

Figure 11

And where photogrammetry may have difficulty where shadows obstruct a view, LiDAR has its own

illumination. It's very likely that miniature LiDAR technologies on UAVs would complement

photogrammetry in the future.

CONCLUSION Using miniature LiDAR technology on UAVs can carry several advantages to imaging projects. First, the

LiDAR can create dense point clouds. UAVs can fly lower than other aerial imaging options while still

reaching angles that would be inaccessible using other methods of imaging. UAVs can cover thousands



11

of meters in a few minutes, and are cost effective for the smaller areas of a few thousand square

meters.

Miniature LiDAR on UAVs can be especially valuable because of the proven algorithms, change

detection, classification and reconnaissance abilities. Given these advantages, LiDAR-UAV adaptations

may prove to be useful for mapping both urban and terrain areas. The technology also lends itself to

situational awareness tasks that require the ability to penetrate vegetation and the exterior of

buildings.

BIOGRAPHY Håkan Larsson has worked at the Swedish Defense Research Agency since 2001. He currently belongs

to the agency's department of Sensor and EW Systems, which uses commercial state-of-the-art sensors

as well its own laser systems to improve situational awareness and data acquisition. Larsson's main

interest is the hardware of 3D laser sensors.

Note: This whitepaper is the product of the transcript of a presentation given at the European LiDAR Mapping

Forum 2014, and available online at www.SPARPointGroup.com. While the speakers are cited here as

contributors, this whitepaper was not written by the contributors or speakers who appeared in the presentation,

nor is it endorsed by the contributors or speakers, or any company, organization or entity they represent. For

more information on how this whitepaper was produced, send inquiries via email to [email protected].

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