LiDAR, an acronym for Light Detection and
Ranging, was originally created as a portmanteau of the
words light and radar. This is a surveying technology that
measures distance by illuminating a target with laser light.
LiDAR increasingly became the catalyst for development of a
wide range of technologies that span numerous STEM
fields. The Global LiDAR market is expected to grow at a
Compound Annual Growth Rate (CAGR) of 19.2% from 2013 to
2018.
Companies that engage in development of LiDAR technologies
as well as usage of it to make advancements in their
respective fields may be eligible for considerable R&D
tax credits.
The Research & Development Tax
Credit
Enacted in 1981, the federal Research and Development
(R&D) Tax Credit allows a credit of up to 13% of
eligible spending for new and improved products and
processes. Qualified research must meet the following four
criteria:
New or improved products,
processes, or software
Technological in nature
Elimination of uncertainty
Process of experimentation
Eligible costs include employee wages, cost of supplies,
cost of testing, contract research expenses, and costs
associated with developing a patent. On December 18,
2015, President Obama signed the bill making the R&D Tax
Credit permanent. Beginning in 2016, the R&D credit can
be used to offset
Alternative Minimum tax and startup businesses can utilize
the credit against $250,000 per year in payroll taxes.
LiDAR Basics
Devices that implement LiDAR essentially fire pulses of
laser light at a surface. A sensor on the device then
measures how long the laser takes to bounce back from the
surface. Since the speed of light moves at a constant, the
distance of how far the laser travels can be highly
accurate. The basic formula that allows LiDAR to give an
accurate measurement is:
Distance = (Speed of Light * Time of
Flight)/2
The speed of light is approximately 186,000 miles per
second. The time of flight is measured by how long it takes
the laser to leave the LiDAR device, hit a surface, and
bounce off that surface back to a sensor on the LiDAR
device. The reason the distance is divided by two is that
the laser is traveling to and from the object. If the
numerator were not divided by two, the distance the laser
traveled would comprise of the entire time of flight, which
demonstrates a reading of double the actual distance of the
object.
One laser leaving a LiDAR instrument is not that impressive,
but when tens of thousands are dispatched, a highly accurate
picture can be rendered. Each laser that hits a surface and
bounces back can be used to measure an accurate distance.
When data from the laser is compiled and manipulated through
advanced algorithms, the points where the lasers strike can
be used to render a 3D image. Thus, when lasers are
dispatched continuously in high volumes per second, a
real-time image can be created. This image is adaptable for
different applications, including virtual mapping for
autonomous videos. The field of photonics and
development of LiDAR are key factors in developing various
technologies.
LiDAR and Autonomous Vehicles
LiDAR has a wide array of applications, but the application
currently receiving the most attention is in autonomous
vehicles. LiDAR is the linchpin of most modern, autonomous
car designs. Coupled with radar, cameras, positioning
systems, and other sophisticated software, driverless
vehicles are intended to greatly influence the market in the
near future. Between 2015 and 2020, the Business Insider
predicted that the self-driving market “will experience a
compound annual growth rate of 134%...when there will be
nearly 10 million cars containing self-driving features on
the road.”
Google empploys LiDAR sensors that cost approximately
$80,000 in its early autonomous vehicle designs. The
LiDAR sensor found atop Google’s round and friendly
prototype provides extreme accuracy of terrain up to 100
meters away. The sensor is a Velodyne 64-beam laser, which
can rotate 360-degrees and take up to 1.3 million readings
per second.
Uber currently utilizes Velodyne’s costly LiDAR in its
autonomous test vehicles. At the same time, Innoviz is
collaborating with Jabil to create a more inexpensive LiDAR
product for self-driving cars. This LiDAR will be a
solid-state device that has extra long detection range of
200m. It will also offer HD, 3D environment
scanning. This is a beneficial advancement for
the future of automated vehicles since it may help achieve
the goal of making driverless vehicles that are more
affordable without compromising on reliability.
Though LiDAR is an excellent tool that allows cars to move
with additional freedoms, it will need to experience
significant price reductions if self-driving vehicles are to
become ubiquitous, as the Business Insider predicted.
Currently, there is a vacuum in the industry where companies
are seeking out LiDARs that cost merely $100 and perform
better, are smaller, and more reliable than the LiDAR
sensors employed, for example, by Google and Uber. In
an effort to attain these goals, developers experiment with
creating solid-state LiDAR systems. Luminar Technologies,
based in Silicon Valley, is expanding the traditional LiDAR
range of 100m to 200m in its new solid-state sensors.
Companies such as Velodyne LiDAR, Inc., based out of Silicon
Valley, are excellent candidates for the R&D tax
credit. Activities involving the minimization of size,
weight, cost, and power consumption of LiDAR sensors are
eligible for federal tax credits as well.
These R&D activities are essential for the future of
self-driving vehicles. Lighter and smaller sensors that use
less power and cost less allow for increased development of
fuel-efficient vehicles. Cost savings in sensors can even be
used to bolster other elements of self-driving cars, such as
power supply.
LiDAR and UAVs
In 2015, approximately $300 million was spent on LiDAR
capable drone development. By 2020, the demand
for LiDAR is forecasted to grow by more than $1 million. In
the past, the cost of investing in LiDAR equipment was
prohibitively expensive. Many companies found it necessary
to rent fixed-wing pilot aircrafts, equipped with LiDAR
technology.
Recent advances in Drone technology, as well as
developments in reducing the size of LiDAR sensors, are
making it possible for LiDAR to reach its full potential.
Many drone manufacturers are developing models that are
LiDAR adaptable.
When LiDAR is used in UAVs, unmanned aerial vehicles, the
UAV’s location must be known at all times. The reason for
this is that the time of flight of the laser would be off if
the movement of the LiDAR sensor from the firing point is
neither precise nor accounted for.
Recent research and development has resulted in various uses
and applications of LiDAR in UAVs. Some include agriculture
and forestry, topography in opencast mining, construction
site monitoring, building and structural inspections,
resource management, collision avoidance, hydrodynamic
modeling, and digital elevation modeling. With the
introduction of LiDAR in UAVs, sophisticated software can
now process LiDAR images to reap numerous benefits that were
previously unattainable.
LiDAR technology has the ability to detect obstacles, which
is used to avoid situations, namely drone collisions. These
sensors have also incorporated optical altimeter technology
that helps agricultural and forestry sectors inspect
vegetation and crops, but also remove aboveground imagery to
get a better view of ground surface area. Such features are
not feasible without the use of LiDAR sensors on UAVs or
drones.
Companies that are employing LiDAR technology to increase
the capabilities of UAVs may be eligible for the R&D tax
credit.
LeddarTech: Headquartered in Quebec City, Canada, this
company is known for making one of the top LiDAR sensors for
UAVs in the industry. Its Vu8 LiDAR Sensor is compact,
solid-state with no moving parts. Unlike its predecessors,
this LiDAR can reach a range of 215 meters. It has a fixed
laser light source, which improves its robustness and
cost-efficiency.
This LiDAR sensor is not impacted by other, disruptive
sensor signals, including direct sunlight and adverse
weather conditions, such as rain and snow. This sensor is
popular for navigation and collision avoidance in drones,
trucks, and construction and mining equipment.
Velodyne: Velodyne creates many of the LiDAR sensors
comprising the marketplace. It makes three of the best
sensors for UAVs, known as HDL-32E, Puck VLP-16, and Puck
Lite. These sensors provide a full 360-degree view of the
environment. The HDL-32E has a rugged design and lower power
consumption, which helps it exceed the demands of
challenging real world autonomous navigation and 3D mobile
mapping. The Puck VLP-16 is the smallest, newest, and most
advanced product from LeddarTech. As the sensor is more
cost-effective than its competitors, Velodyne intends to
mass produce it. The sensor offers real-time features,
360-degree horizontal field of view, 3D distance, and
calibrated reflectivity measurements. Finally, the Puck Lite
is even lighter than the Puck VLP-16, weighing 590 grams.
Other than weight, there is no significant difference
between this version and the VLP-16.
LiDAR and Manufacturing
LiDAR technology will also change the way that
manufacturing is conducted. There is recent demand for
Automation in manufacturing, which is necessary for American
companies to remain competitive in the global marketplace.
In 2015, Amazon announced plans to hire 6,000 new warehouse
workers. The same week of this announcement, Amazon
sponsored a competition at The IEEE’s International
Conference on Robotics and Automation in Seattle, WA. The
purpose of the competition was for contestants to design a
robot capable of autonomously picking up products and
packaging them for shipment. Currently, there are no
industrial robots capable of recognizing even a small
percentage of products that Amazon sells.
Industrial robots have a hard time grasping a wide
range of differently shaped items. The geometries of the
items differ, which makes it more challenging for the robot
to determine the proper methodology to pick up the right
product for packaging and shipment.
Of the many different approaches explored to solve this
debacle, a popular one is to utilize LiDAR sensors.
Companies like Boeing believe that “3D LiDAR is the key to
everything.” 3D LiDAR has the potential to permit
manufacturing robots to understand the world around them. As
a result, manufacturing robots can use LiDAR sensors to
create a succession of 3D maps over time. These maps can
then be analyzed to find differences, which would give
manufacturing robots the ability to recognize when objects
move and which ones are moved. The robot would simply
identify and compare the differences between the 3D maps
over time to be more productive and efficient.
Developments in LiDAR technology ought to revolutionize the
manufacturing industry. Any firm employing LiDAR to advance
robotic awareness and object identification capabilities is
eligible to apply for the R&D tax credit.
University Efforts
University of California,
Berkley
The need for more inexpensive laser technology in autonomous
vehicles sparked a race to develop the next generation of
LiDAR technology. The University of California, Berkeley is
at the forefront of the competition. Berkley is developing a
new self-sweeping laser that can significantly shrink 3D
mapping systems.
The new approach automates the way a light source changes
wavelength as it passes over a terrain. When LiDAR sensors
are at work, they must be able to continuously change
frequency of the shooting lasers so the difference between
the incoming reflected light and outgoing light can be
calculated. The reason this advancement is groundbreaking is
because the new system can be powered simply by an AA
battery. As a result, a LiDAR sensor can be brought down
from the size of a shoebox to something condensed enough to
fit on a Smartphone or UAV.
MIT
Massachusetts Institute of Technology has been making
advances in laser and 3D imaging technology. Recently, MIT
researchers developed a polarization technique to increase
the resolution of a conventional 3D-imaging device by a
factor of 1,000. The new technique employs Microsoft Kinect,
a video game accessory, and different polarized filters to
determine the precise orientation of light that bounces off
an object.
Carnegie Mellon University
Carnegie Mellon is well known in the world of robotics and
autonomous vehicle navigation. This private institution
believes LiDAR is a key component in the navigation systems
of self-driving vehicles. It is currently engaged in
researching optimal LiDAR sensor configuration. The premise
of this research is to create a framework that permits
mechanisms with multiple LiDAR sensors configured with
different settings to be more effective.
Computation Increases LiDAR’s
Effectiveness
Recent advancements in the mechanical aspects of LiDAR
sensors have been sudden, but what truly advanced the
capabilities of LiDAR sensors is the computing power behind
it. Simply put, the more photons that are dispersed from a
LiDAR sensor, the better. Its accuracy will significantly
increase when the amount of photons fired per second
increases. If all data points collected are not processed
rapidly into actionable data, then it will not be beneficial
to its users. The future of LiDAR is intertwined with the
development of processors and algorithms that better wrangle
the massive data sets that LiDAR sensors produce.
The U.S military is in possession of a highly advanced
“microchip bearing the largest every array of pixels that
detect just one photon a piece–more than 16,384 pixels in
all.” This system is designed by Lincoln Laboratory, a
federally funded R&D center run by MIT. There is no
available imagery of the new, functioning system, but its
power and capability can be extrapolated based off earlier
system generations.
After the 2010 Haiti earthquake, an earlier version of the
system was installed on a commercial Jet. During a
single pass at 10,000 feet above Port-au-Prince, Haiti, the
jet captured snapshots of 600 square meters of the city at a
resolution of 30 centimeters. This snapshot’s clarity could
even demonstrate the height of rubble in the streets. What
is remarkable is that the clarity of this legacy LiDAR
system was made with one-quarter of the pixels equipped on
the new system.
LiDAR and Wind Farm Optimization
LiDAR is changing the way people approach renewable
energies. Wind energy is a promising energy source
that is gaining significant traction. For wind power to
become more readily adopted, wind farms ought to be more
energy efficient. Now, significant acreage is required to
meet commercial and residential power needs. Wind turbines
are also costly. When wind farms are built it is crucial
they produce as much energy as possible will being efficient
and cost effective. LiDAR can help achieve this goal.
LiDAR is currently advantageous in measuring wind flow.
Normally, when surveying a site for a wind farm, models are
created to determine potential energy generation. When LiDAR
measurements are integrated into the modeling process,
models become significantly more accurate and descriptive.
Such an increase in accuracy allows for the selection of a
location that is guaranteed to produce more wind energy.
This in turns reduces the uncertainty of energy yield, which
also reduces uncertainty in the investment.
LiDAR is also applicable to wind farms monitoring
performance and ensuring optimization. LiDAR can be used to
gather data on wind conditions that impact the performance
of wind turbines. In cases where LiDAR sensors detect
conditions such as wind shear and strong gusts of wind,
turbine control hardware can be directed to regulate the
machines to operate in ways that protect the turbine from
potential damage.
Companies that engage in efforts to increase wind turbine
performance using LiDAR technology can apply for the federal
R&D tax credit.
LiDAR and Spaceflight
LiDAR’s accuracy in range finding makes it ideal for
spaceflight. When it comes to spaceflight, LiDAR is
beneficial in orbital element calculation, proximity
operations, station keeping of spacecrafts, and atmospheric
studies conducted from space.
Many researchers in the Spaceflight industry use LiDAR
technologies in revolutionary applications. NASA, the
most prominent in the spaceflight community, is currently
collaborating with DRS Technologies, based out of Virginia,
to create a mid-infrared detector. This detector is made
from Mercury-Cadmium-Telluride. What makes this detector
highly efficient is that it can process returning infrared
signals at a single photon level. The new detector is the
world's first photon counting detector. It can register
mid-infrared wavelength bands, which will greatly increase
the performance of a multitude of remote sensing
applications.
LiDAR is even being used by Space X, a privately held space
agency. Space X’s CRS-5, which was launched in 2015, was
equipped with LiDAR technology. Such instruments were
mounted on the CRS-5, giving it the capability to measure
the altitude distribution of aerosols in the Earth’s
atmosphere. This applicability in atmospheric physics helps
measure and determine the oxygen, nitrogen, and other gas
particle contents in the middle and upper atmospheres
Finally, LiDAR was employed in space exploration, namely
that of Mars. The technology was used to create a
topographic map of the planet. Because of this success, NASA
employs LiDAR technology in its Phoenix Lander to determine
snow precipitation in the Mars’ atmosphere.
General LiDAR Applications
As previously mentioned, LiDAR usage is growing in varying
industry sectors. They are popular in agriculture and forest
planning management. Because LiDAR helps develop advanced
elevation maps, farmers can convert this into slope and
sunlight exposure maps. This helps farmers create high,
medium, and low crop production areas to save on costly
fertilizer and other farming techniques. In forest planning,
it facilitates the measurement and understanding of vertical
canopy structures and its density.
LiDARs are beneficial in water management as well. Watershed
and stream delineation benefit from the use of LiDARs.
Coupled with GIS software, one can calculate the watershed
for a specific channel or determine stream channels for over
land flooding. Surveying rivers is made possible with the
water penetration green light of LiDAR. This information
helps determine depth, flow strength, and width of the
river. Now, engineers can produce more advanced river models
as well as floor way and fringe maps. This same
feature works for marine engineers studying the ocean.
Engineers are beginning to utilize LiDARs for Integrated
Storm Water Management planning, another way to manage
rainwater. This process balances land use planning, storm
water engineering, floor and erosion protection, and
environmental protection. Elevation maps are crucial for
this process, which is made possible with accurate and
precise data from LiDAR sensors.
Finally, the oil and gas industry implements LiDAR sensors
to detect molecular content of the atmosphere. With
technology called DIAL, Differential Absorption LiDAR, teams
trace the amount of gas populating an area above the
hydrocarbon region. As a result, experts can more accurately
determine the location of oil and gas deposits. Similarly,
miners employ LiDAR to measure ore volume via a series of
photos of the extraction space.xxv
Conclusion
From manufacturing to meteorology, LiDAR is an integral
technology for many disciplines. LiDAR technologies are
becoming lighter, more accurate, and cost efficient. As
LiDAR advancements becomes more refined and ubiquitous, its
applications will expand. Companies with a direct hand in
the progression of LiDAR as well as those using LiDAR to
supplement products and research efforts can take advantage
of the R&D tax credit. Companies can use the savings
generated from the credit to further fund their research and
advance organizational goals pertaining to LiDAR
innovations.