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In From Around the Web, Science & Technology January 18, 2017 David Aragorn11 Views 0 comments

Pentagon successfully tests micro-drone swarm

The Pentagon may soon be unleashing a 21st-century version of locusts on its adversaries after officials on Monday said it had successfully tested a swarm of 103 micro-drones.

The important step in the development of new autonomous weapon systems

was made possible by improvements in artificial intelligence, holding open the

possibility that groups of small robots could act together under human

direction.

Military strategists have high hopes for such drone swarms that would be

cheap to produce and able to overwhelm opponents’ defenses with their great

numbers.

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From Around the Web, Science & TechnologyJanuary 18, 2017

Pentagon successfully tests micro-drone swarm

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The test of the world’s largest micro-drone swarm in California in October

included 103 Perdix micro-drones measuring around six inches (16

centimeters) launched from three F/A-18 Super Hornet fighter jets, the

Pentagon said in a statement.

“The micro-drones demonstrated advanced swarm behaviors such as

collective decision-making, adaptive formation flying and self-healing,” it said.

“Perdix are not pre-programmed synchronized individuals, they are a collective

organism, sharing one distributed brain for decision-making and adapting to

each other like swarms in nature,” said William Roper, director of the

Pentagon’s Strategic Capabilities Office. “Because every Perdix communicates

and collaborates with every other Perdix, the swarm has no leader and can

gracefully adapt to drones entering or exiting the team.”

Defense Secretary Ash Carter—a technophile and former Harvard

professor—created the SCO when he was deputy defense secretary in 2012.

The department is tasked with accelerating the integration of technological

innovations into the US weaponry.

It particularly strives to marry already existing commercial technology—in this

case micro-drones and artificial intelligence software—in the design of new

weapons.

Originally created by engineering students from the Massachusetts Institute of

Technology in 2013 and continuously improved since, Perdix drones draw

“inspiration from the commercial smartphone industry,” the Pentagon said.

Source: Phys.org

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Confirmed: This giant squid video is the REAL thing

Drone-photography company fined $200,000 by FAA

Learn More

Bart Jansen , USA TODAY Published 1:16 p.m. ET Jan. 17, 2017 | Updated 1:41 p.m. ET Jan. 17, 2017

WASHINGTON – A drone-photography company has agreed to pay a $200,000 penalty to settle

allegations without acknowledging violating federal regulations for flying remote-controlled aircraft for years

over New York and Chicago, the Federal Aviation Administration announced Tuesday.

SkyPan International agreed to pay an additional $150,000 if it violates the settlement during the next year, and

another $150,000 if fails to comply with the terms of the agreement, the FAA announced.

The FAA initially sought to fine SkyPan International $1.9 million, in the largest case yet against a drone

company.

"While neither admitting nor contesting the allegations that these commercial operations were contrary to FAA regulations, SkyPan wishes to resolve this

matter without any further expense or delay of business," the company said in a statement. "In exchange, the FAA makes no finding of violation."

FAA seeks record $1.9 million fine from drone company SkyPan

(http://www.usatoday.com/story/news/2015/10/06/faa-drone-fine-skypan-19-

million/73441850/)

In the civil case filed in October 2015, the FAA alleged that SkyPan flew 65 unauthorized flights between March 21, 2012, and Dec. 15, 2014. SkyPan

lacked the proper certificate and registration for the flights, didn't have special permission from FAA or air-traffic control and the aircraft weren't equipped

with equipment to signal their presence to other aircraft, the FAA alleged.

SkyPan applied on Dec. 22, 2014, for an FAA exemption to fly drones, which the FAA approved April 17.

At the time of the disputed flights, FAA was developing its comprehensive regulations for commercial drones. The FAA began issuing waivers for

commercial flights in September 2014 and completed regulations for drones weighing up to 55 pounds in June 2016.

SkyPan said it has been conducting aerial photography above private property in urban areas for 28 years, using both full-size helicopters and remote-

controlled helicopters. The flights were typically over dirt, grass or paved lots to show high-rise views that assist developers with design plans for new

buildings, according to the company's application.

The images have been used to sell or lease $55 billion of commercial and residential real estate since 1988, according to the application for a waiver.

Clients included developers Durst, Extell, Hines, Howard Hughes, Vornado and Zeckendorf.

FAA’s drone regulations will allow SkyPan and others to fly in controlled airspace if authorized by air-traffic controllers. SkyPan in its statement urged the

industry to work collaboratively with the FAA to balance commerce with safety.

"SkyPan has never had an accident," the company said in resolving the FAA complaint. "SkyPan continues to strive to maintain the utmost levels of

safety, security, and privacy protection in its operations."

Read or Share this story: http://usat.ly/2k1kMSm

(Photo: Andrew Harnik, AP)

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Page 1 Copyright: Pix4D

I. Introduction

The Royal Canadian Mounted Police started using Unmanned Aerial Vehicles to help them with their

work on collision and crime scene investigations. It allows the investigations to be conducted under all

weather conditions and provides broader views than the traditional procedures.

This past September, an experimental project was organized by the Royal Canadian Mounted Police

(RCMP) and Pix4D, using UAV models from Draganfly and Aeryon Labs to acquire images of a staged car

accident scene from low altitude. The images were processed by Pix4Dmapper to reconstruct the three-

dimensional scene. In this article, we compare the time spent and accuracy between UAV mapping

and traditional procedures, including laser scanner.

The project aims to propose a solution protocol for accident scene investigations. Additionally, by

including the accuracy and reliability of the output results, it ensures not only that the whole process is

efficient and accurate but also that the reconstruction results can be eventually used as admitted

evidence in court.

II. Presentation of the Project

The project took place in Regina, Canada. A staged car accident scene was set up to reproduce a crash

of two vehicles with a person fallen out of one of the vehicles. The RCMP took photographs and

measurements before anything was moved. The yellow plastic evidence markers indicated where each

piece of evidence was found.

Aeryon Labs and Draganfly rotary-wing UAVs were used to acquire images with very high overlap and

ground sampling distances of 0.6 and 0.9 centimeters respectively. Both UAVs acquired oblique photos

by flying a few circles around the scene as well as nadir photos with grid flight plans above the crime

scene. Both flights lasted between ten and twenty minutes. A total of 225 images from Aeryon Labs and

212 images from Draganfly were obtained during the flights.

A few on-site measurements were made by the police. GPS measurements of the object corners and

the evidence markers were used as ground control points, and tape measurements between the markers

were recorded for further assessment of the final results.

Pix4Dmapper’s total processing time was approximately two hours on a laptop with a core i7 and 8GB

RAM. A densified point cloud, digital surface model (DSM) and orthomosaic were generated. Annotation

and measurements were directly made in the software user interface.

A New Protocol of CSI For The Royal Canadian Mounted Police

Page 2 Copyright: Pix4D

III. Data Acquisition

The total pre-flight preparation time was approximately ten minutes. Both UAV models weigh less than

two kilograms and thus are light enough to be easily unpacked and operated by a single person. Once the

flight plan set, it took less than twenty minutes to complete the designed flights. For the proposed protocol,

the entire on-site process time is estimated within thirty minutes, excluding optional measurements.

Nadir images taken with grid flight plans achieved high overlaps and eliminated systematic errors. A few

circular flights were performed to obtain oblique images of the most focused area in order to cover as

many facades as possible. With a flying height of approximately forty meters above the ground, images

with a ground sampling distance of less than one centimeter were collected. These images provided

accurate and detailed information of the collision.

In order to improve the global accuracy of the final results (which is optional), several points were

measured with kinetic GPS and total station. These points were picked from corners of the vehicles, the

feature objects, and the evidence markers. They were imported into the software and used either as

ground control points, manual tie points or check points.

In addition to the measurements mentioned above, a

terrestrial laser scanner was set up in several locations to

scan over the entire scene, to be used for quality

assessment of the UAV results.

The laser-scanned point cloud was compared with the

Pix4Dmapper point cloud in respect to their density,

accuracy and how they fit the actual needs.

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IV. Comparison with Traditional Procedures

Traditionally, the collision investigation workflow adapted by most police departments - including the

RCMP - uses tapes, GPS and laser scanners. Tapes and GPS provide a limited number of measurements.

They are written down in field books, and it is not easy to recall precisely where the measured spots were

located. Plus, these measurements may easily contain manual mistakes and are not accessible in all

situations.

Usage of laser scanners is expensive and time consuming, and the delicate instruments need to be

operated by trained professionals. Some other issues to take into consideration are the obstruction of

laser beams and the difficulty of finding appropriate locations to set up the scanners, resulting in missing

point cloud data of extremely important information in some hard-to-reach yet focused areas.

One or a combination of the three principal measuring methods are used depending on

circumstances. Sometimes one method is enough to cover the whole scene while in other conditions the

combination of two or more of them is required to complete the tasks.

New UAV era

UAVs provide more practical solutions as they respond faster to emergency cases. They are already

broadly used for natural disaster monitoring, and can also serve as an ideal reconstruction workflow for

accident investigations.

We propose the use of UAVs for several reasons - rather than choosing case-by-case from the

measuring methods - as it is more likely to fit all solutions. For wide-coverage accident scenes, UAVs save

hours or even days on the time spent gathering data and

measurements.

The proposed protocol contains three simple steps:

1) UAV preparation and data acquisition

2) 3 to 5 tape or GPS measurements

for quality improvement and assessment

3) Pix4Dmapper processing with a fully automatic workflow

The whole procedure, including the on-site flight and an additional ten minutes of optional but

recommended measurements for quality assessment, can be completed right after the accident occurred.

For this project, the total processing time of Pix4Dmapper was approximately two hours. After processing,

the whole scene was reconstructed and the terrain model, point clouds, and orthomosaic were exported.

Annotation and measurement were then directly performed in the software.

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V. Accuracy Assessment with On-site Measurement and Laser Scanner Result

a) Compare UAV+Pix4Dmapper results with tape measurements

Eight evidence markers, labeled with the

numbers 1 to 8, had their positions surveyed

by GPS and thus were with known

coordinates. Tapes were used to measure

the following distances between markers:

1-2, 3-4, 5-6, and 7-8.

The same distances were also measured

by the measuring tools in Pix4Dmapper.

These two types of measurements were

compared with the same distances

calculated directly from the known

coordinates of markers.

b) UAV+Pix4Dmapper results in RCMP Truck Dimensions

Images acquired by the UAVs were processed and the three-

dimensional scene was reconstructed by Pix4Dmapper. As seen

in the lower graphs, we measured the width, length, and height

of the RCMP truck directly in the software, and the results

exactly match the real RCMP truck dimensions.

These results confirm the high accuracy of Pix4Dmapper, both

for its processing and measuring capabilities.

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c) Compare UAV+Pix4Dmapper results with laser scanner measurements

Laser scanner measurements are well-known to provide accurate point clouds and to have high

penetration through objects. In this example, we could actually see some points inside the vehicles.

However, it took more preparation time than the UAVs and the scanner's set-up position and scanning

angles were not flexible. From the graphs below, we can observe that the scanner obtained much fewer

points. Another difficult problem to solve was the obstruction of views, resulting in lack of details in the

focused area around the body.

Rotary wing UAVs like the Draganfly and Aeryon Labs systems are capable of getting very close to the

aim with good control. The number of points generated by Pix4Dmapper for the point cloud depends on

the image resolution, image quality and the program settings. For a dataset of less than one centimeter

GSD, Pix4Dmapper provides both high accuracy and fine details of the scene.

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VI. Additional Showcase - RCMP Office Reconstruction

In addition to the collision scene project, two data sets from the RCMP office were acquired. The outdoor

images were taken from various heights above and around the office building by UAVs and hand-held

cameras (Canon 6D and GoPro); the indoor images were taken only by hand-held cameras (GoPro),

collecting information from the corridors and from one office. Outdoor flight plans were following:

Indoor images were acquired while passing through the corridor and entering an office inside the building.

The photographed office was located to the right of the corridor, as seen in the small circle on the image

position path here under. Sub-projects of both the inside and outside of the building were processed

separately and then merged into one project.

Processing with Pix4Dmapper required less than two hours for the

outdoor data set containing 421 images. For the indoor data set of

139 images, it required only ten minutes to reconstruct and half an

hour for point densification. Manual points were added in the

projects and clicked manually to help with the merging process.

T h e two sub-projects were then merged successfully, as seen in

the rayCloud editor of Pix4Dmapper and the windows and door

shared by both data sets were perfectly matched. We also see from

the graphs below that the image positions of the indoor data set

correctly match the outdoor reconstruction.

The merged project kept the same accuracy as the individual

projects and we were able to measure the indoor objects directly in

the software, for example the magazine width displayed in the figure

on the right.

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VII. Conclusion ���� ����������

Unmanned Aerial Vehicles have become the most practical solution in many urgent cases. They can be

used to search and save survivors in the wilderness, to collect updated photos or videos for monitoring

natural disasters and to reconstruct traffic collision or crime scenes to be presented in court. These are

only some examples of conditions where timeliness is the most critical concern.

The combination of UAVs for image acquisition and Pix4Dmapper for converting images into results

provides a complete solution to reconstruct accident and crime scenes and solves vital issues not covered

by traditional methods.

Why use UAVs+Pix4Dmapper?

They provide angles with multiple views from the ground as well as from the air. Obtaining information

from a bird's-eye view is very helpful as it solves important issues when evidence is spread out and it is

difficult to get a good perspective from ground level. Previously, helicopters were used to provide such

complimentary information. However, organizing an available copter to cover the scene sometimes

takes up to several days and by that time, outdoor evidence already might have been altered or washed

out due to weather conditions (heavy rain or snow).

Compared to other precision instruments such as laser scanners, the cost of execution and

maintenance of UAV mapping is much lower. Packed in an easily transportable case and a weight of

under two kilograms, UAVs can be carried everywhere. And UAVs are ready to fly after some minutes of

assembling only. Such small systems are also easier to use and maintain, saving expenses and time

spent on training staff.

Using UAVs and Pix4Dmapper for reconstructing accident and crime scenes provides an immediate response, saves time and expenses and offers highly accurate outputs. Generated results are available permanently and the files and make measurements anytime he/she requires to. Actual scenes are preserved in 3D and with detailed information within centimeter accuracy.

Applies to all conditions

Efficient and time saving, immediate response

High accuracy for measurements

Views from all angles, no missing details

Easy to operate and maintain, less training needed

Both outdoor and indoor reconstruction, seamless merging

Permanent preservation of data and reconstructed scene