PRE2018 3 Group9

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Contents

Preface

Group Members

Name Study Student ID
Claudiu Ion Software Science 1035445
Endi Selmanaj Electrical Engineering 1283642
Martijn Verhoeven Electrical Engineering 1233597
Leo van der Zalm Mechanical Engineering 1232931

Initial Concepts

After discussing various topics we came up with this final list of projects that seemed interesting to us.

  • Drone interception
  • A tunnel digging robot
  • A fire fighting drone for finding people
  • Delivery uav - (blood in Africa, parcels, medicine, etc.)
  • Voice control robot - (general technique that has many applications)
  • A spider robot that can be used to get to hard to reach places

Chosen Project: Drone Interception

Introduction

According to the most recent industry forecast studies, the unmanned aerial systems (UAS) market is expected to reach 4.7 million units by 2020.[1] Nevertheless, regulations and technical challenges need to be addressed before such unmanned aircraft become as common and accepted by the public as their manned counterpart. The impact of an air collision between an UAS and a manned aircraft is a concern to both the public and government officials at all levels. All around the world, the primary goal of enforcing rules for UAS operations into the national airspace is to assure an appropriate level of safety. Therefore, research is needed to determine airborne hazard impact thresholds for collisions between unmanned and manned aircraft or even collisions with people on the ground as this study already shows.[2].

With the recent developments of small and cheap electronics unmanned aerial vehicles (UAVs) are becoming more affordable for the public and we are seeing an increase in the number of drones that are flying in the sky. This has started to pose a number of potential risks which may jeopardize not only our daily lives but also the security of various high values assets such as airports, stadiums or similar protected airspaces. The latest incident involving a drone which invaded the airspace of an airport took place in December 2018 when Gatwick airport had to be closed and hundreds of flights were cancelled following reports of drone sightings close to the runway. The incident caused major disruption and affected about 140000 passengers and over 1000 flights. This was the biggest disruption since ash from an Icelandic volcano shut down all traffic across Europe in 2010.[3]

Tests performed at the University of Dayton Research Institute show the even a small drone can cause major damage to an airliner’s wing if they meet at more than 300 kilometers per hour.[4]

There are other areas in which drones can have a big impact for users, society and enterprise alike. To summarize these are the key domains impacted by the rise of drones:

  • Airport Security
  • Drone Terrorism
  • Privacy Violation
  • Drone Spying (on governments for intelligence gathering)

Problem Statement

The problem statement is: How can unmanned aerial systems (UAS) be used to quickly intercept and stop other unmanned aerial vehicles (UAV) in airborne situations.

A UAV is defined as an unmanned aerial vehicle and differs from a UAS in one major way: a UAV is just referring to the aircraft itself, not the ground control and communications units.[5]

Objectives

  • Determine the best UAS that can intercept another UAV in airborne situations
  • Improve the chosen concept
  • Create a design for the improved concept, including software and hardware
  • Build a prototype
  • Make an evaluation based on the prototype

Project Organisation

Approach

The aim of our project is to deliver a prototype and model on how an interceptive drone can be implemented. The approach to reach this goal contains multiple steps.

Firstly, we will be going to research papers which describe the state of art of such drones and its respective components. This allows our group to get a grasp of the current technology of such a system and introduce us to the new developments in this field. This also helps to create a foundation for the project, which we can develop into. The state of art also gives valuable insight into possible solutions we can think and whether their implementation is feasible given the knowledge we possess and the limited time. The SotA research will be achieved by studying the literature, recent reports from research institutes and the media and analyzing patents which are strongly connected to our project.

Furthermore, we will continue to analyze the problem from a USE – user, society, enterprise – perspective. An important source of this analysis is the state of art research, where the impact of these drone systems in different stakeholders discussed. The USE aspects will be of utmost importance for our project as every engineer should strive to develop new technologies for helping not only the users but also the society as a whole and also avoid the possible consequence of the system they develop. This analysis will finally lead to a list of requirements for our solutions. Moreover, we will discuss the impact of these solutions on the categories listed prior.

Finally, we hope to develop a prototype for an interceptor drone. We do not plan on making a physical prototype as the time of the project is not feasible for this task. We plan on creating a 3D model of the drone and simulating it, showcasing its functionality in real life. To complement this, we also plan on building an Android application, which serves as a dashboard for the drone tracking different parameters about the drones such as position and overall status. To realize this a list of hardware components will be researched, which would be feasible with our project and create a cost-effective product. Concerning the software, a UML diagram will be created first, to represent the system which will be implemented later on. Together with the wiki page, these will be our final deliverables for the project.

Below we summarize the main steps in our approach of the project.

  • Doing research on our chosen project using SotA literature analysis
  • Analyzing the USE aspects and determining the requirements of our system
  • Consider multiple design strategies
  • Choose the Hardware and create the UML diagram
  • Work on the prototype (3D model and mobile application)
  • Evaluate the prototype

Milestones

Within this project there are three major milestones:

  • After week 2, the best UAS is chosen, options for improvements of this system are made and also there is a clear vision on the user. This means that it is known who the users are and what their requirements are.
  • After week 5, the software and hardware are designed for the improved system. Also a prototype has been made.
  • After week 8, the wiki page is finished and updated with the results that were found from testing the prototype. Also future developments are looked into and added to the wiki page.

Deliverables

  • This wiki page, which contains all of our research and findings
  • A presentation, which is a summary of what was done and what our most important results are
  • A prototype

Planning

The plan for the project is given in the form of a table in which every team member has a specific task for each week. There are also group tasks which every team member should work on. The plan also includes a number of milestones and deliverables for the project.

Name Week #1 Week #2 Week #3 Week #4 Week #5 Week #6 Week #7 Week #8
Research Requirements and USE Analysis Hardware Design Software Design Prototype / Concept Proof Reading Future Developments Conclusions
Claudiu Ion Make a draft planning Add requirements for drone on wiki Regulations and Present Situation Write pseudocode for interceptor drone Mobile app development Proof read the wiki page and correct mistakes Review wiki page Make a final presentation
Summarize project ideas Improve introduction Wireframing the Dashboard App Build UML diagram for software architecture Review wiki page
Write wiki introduction Check approach Start design for dashboard mobile app Mobile app development
Find 5 research papers
Endi Selmanaj Research 6 or more papers Elaborate on the SotA Research the hardware components Work on the drone model Work on 3D drone model / prototype Reviewing the Wiki and fixing spelling errors Finalise the Wiki Page Work on final presantation
Write about the USE aspects Review the whole Wiki page Purchase or request the needed hardware Work on the code needed for the electronics Finish the simulation Work on the layout of the Wiki Check on the relaisation of all objectives
Improve approach Draw the schematics of electronics used Start with the simulation Expand on the material on the Wiki more
Check introduction and requirements
Martijn Verhoeven Find 6 or more research papers Update SotA Research hardware options Start on 3D model of drone Work on 3D model Review wiki page Finalise wiki page
Fill in draft planning Check USE Start thinking about electronics layout Make a bill of costs and list of parts Deliver 3D model of drone
Write about objectives
Leo van der Zalm Find 6 or more research papers Update milestones and deliverables Start on 3D model of drone Work on 3D model Review wiki page Continue tasks from week 7 Finish all lose ends
Search information about subject Check SotA Research hardware components Make a bill of costs and list of parts Put in new devellopmets from week 3, 4 and 5 Write future developmetns Write conclusion/results part
Write problem statements USE analysis including references Start looking at the final presentation
Write objectives
Group Work Introduction Expand on the requirements Research hardware components Interface design for the mobile app Start working on the visualisation
Brainstorming ideas Expand on the state of the art Research systems for stopping drones Start working on drone prototype
Find papers (5 per member) Society and enterprise needs Start working on 3d drone model
User needs and user impacts Work on UML activity diagram Start working on the simulation
Define the USE aspects Improve week 1 topics
Milestones Decide on research topic Add requirements to wiki page USE analysis finished Provide a bill of costs and list of parts Mobile app prototype finished Visualisation finished
Add research papers to wiki Add state of the art to wiki page UML activity diagram finished 3D drone model finished
Write introduction for wiki Research into building a drone
Finish planning Research into the costs involved
Deliverables Mobile app prototype Final presentation
3D drone model Wiki page

USE

There are a lot of stakeholders associated with the use of interception drones. It affects its users, the society, the enterprise and the engineers. Each of these stakeholders experiences different concerns, which are going to be elaborated separately.

Users

The primary user of the interception drone will be the government. We can divide this over three different branches, namely the police, the secret service and the army. If we look at the police this interception drone can be quite helpful technology. Problems with drones are new and occur more often. It is hard for the police to keep up with all the upcoming technologies. But they have to, because some upcoming technologies can be used with malicious intentions. For example drones. They can violated restricted airspaces or be used to spy on people and these actions are rather simple to accomplish. The policy has to be able to stop people from violating laws with respect to drones. And also they want to do this independent. For the government to have a special drone interception unit would not be efficient. First of all because the interception drone is easy to use and it is not necessary to train specialized unit for it. And second of all, drone incident happen a lot and also differ from size. Most citizens don’t know the laws with respect to drones. To use a specialized unit for every little incident is not efficient. That is why the policy should get interception drones and learn how to use them, with a little practice.

Also for the secret service this interception drone can be useful. Drones are more often used on governmental spying, with the intent of getting classified information on places where it is hard for men to reach. The secret service wants that the society remains safe and doesn’t feel threatened by another one. The use of interception drones can help with this. They can take down drones which are spying and trying to get classified information.

And as last the army can use interception drones. They armies biggest concern is keeping peace and prevent human casualties. This can be done by preventing terroristic attacks or stand their ground at the battlefield in times of war. First off all the interception drone can be a great technology to prevent and take down terroristic attacks. Terrorist are becoming smarter and smarter and we have to be sure that we are one step ahead. It did not occur a lot yet but the changes are that terrorist are going to use drones. This gives them the advantage of not risking their own lives. If we do not prepare know, terrorist are going to make use of this. Interception drones can take down armed drones, but also secure the area at big events. Deploying agents on the ground at big events is not going to make a difference when drones are used by terrorists. But also on the battlefield interception drones could be useful. If we look at all the wars in history, it proves that technology always plays a big role. Think of the V2-rockets that were used by the Nazi’s. Having an advance in technology, gives an advance on the battlefield. The army needs to be prepared if another army is using drones as weapons and with the interception drone they could be.


Another user of interception drones are large organizations and firms, that could be a target of aerial assault or intervention by drones or other flying objects. Organizations that possess high sensitivity information or want to protect very highly individuals to their business have to make their best efforts to guarantee the security of such assaults. This is the case that interception drones would be the best solution, as they offer high flexibility. Flying drones can also possess risk on the operation of such places as airports, causing millions of dollars of costs and huge delays, such as in the example of Gatwick Airport in London, where flights were delayed for 24 hours, because of an unidentified drone flying around the airport. This could have easily been avoided with the use of interception drones, saving the airport a lot of money and guaranteeing the passengers to arrive at their destination on time.

Interception drones can also find use by individuals who are prone to get targeted by paparazzi and the media to get more information on their private life. There have been a lot of cases where drones have been used to interfere with the private life of celebrities. An example of that and successful interception of the drone is the case of Roman Abrahamovich, a billionaire from Russia, whose yacht was approached by a drone operated by a person standing on the shore [6]. The drone was intercepted by a machine, which intercepted the RC signals, but was manually operated from the employees of the yacht. An interception drone would be a better solution in this case, as it could offer an autonomous solution even when no one is paying attention or when it is night time and visibility is a problem. But this is going to be the smallest group of users, because these interception drones come with responsibility and also a price tag. This drones can be used as weapons and we do not want to give them away. We see this problem at the moment with regular drones, anyone can get one for a decent amount of money and can use them for bad intentions like what happened at the Gatwick Airport in London.

Society

First of all drones can provide security. The government can use this drones to take down drones with malicious intentions. Think of an terroristic attack, or an attack on private governmental information. Also interception drones can withstand violation of individual privacy. They can guarantee the members of society that their information and security are being protected and it adds trust to the society in the government.

Secondly, the use of interception drones can be an economical benefit. In a way of preventing that an airport has to ground over a thousand flights in two days because of drones that were disrupting the air traffic what happened at the Gatwick airport in London. In the future this can happen more often because the criminals only need a drone to stop an entire airport from functioning. Not only drones can be a threat to airports, but think of train stations and high ways. It is clear that with the use of drones traffic can easily disrupted and this is bad for the economy. Interception drones can be a solution to all these problems, because the drones that create a threat can be taken done.

Enterprise and the Engineers

To enterprises, the implementation and commercialization of interception drones would mean higher income and profits. It would create a sub-industry to the already growing drone industry. Also, since the majority of buyers would be governments, big organizations or rich individuals, it could turn big profits for the enterprises.

Although it can be highly lucrative for the enterprise, such interception drones can possess difficulties for the engineers designing them. Firstly, the engineers should make sure that the interception drone identifies all the time the presence of another drone and false positives are as low as possible, as they can result in high costs. Another challenge that the implementation of interception drones is the flight time that a drone can have. Since they require a lot of power at the moment drone flight times are almost most of the time under 40 minutes and it is also the case in these drones as if they want to actually intercept an attacking drone they need to be really powerful. Engineers might need to develop a method so that the drones spend as little energy as possible or that they can hold more battery capacity.

Requirements

In order to better understand the needs and design for an interceptor drone, a list of requirements is necessary. There are clearly different ways in which a rogue UAV can be detected, intercepted, tracked and stopped. However, the requirements for the interceptor drone need to be analyzed carefully as any design for such a system must ensure the safety of bystandars and minimize all possible risks involved in taking down the rogue UAV. Equally important are the constraints for the interceptor drone and finally the preferences we have for the system. We will now give the RPC table for the autonomous interceptor drone.

ID Requirement Preference Constraint Category
R1 Detect rogue drone LIDAR system for detecting intruders Does NOT require human action Software
R2 Autonomous flight Fully autonomous drone Does NOT require human action Software & Control
R3 Object recognition Accuracy greater than 90% Uses AI bounding box algorithm Software
R4 Detect rogue drone's flying direction Accuracy greater than 70% Software & Hardware
R5 Detect rogue drone's velocity Accuracy greater than 90% Software & Hardware
R6 Track target Tracking targer for at least 10 minutes Allows for operator to correct drone Software & Hardware
R7 Velocity of 40 km/h Drone is as fast as possible Hardware
R8 Flight time of 10 minutes Flight time is maximized Hardware
R9 FPV live feed (with 60 FPS) Drone records and transmits flight video Records all flight video footage Hardware
R10 Camera of 1080p Flight video is as clear as possible Hardware
R11 Stop rogue drone Is always successful Can NOT be violet or endanger others Hardware
R12 Stable connection to operation base Drone is always connected to base If connection is lost drone buffers data Software
R13 Sensor monitoring Drone sends sensor data to base and app All sensor information is sent to base Software
R14 Return to home functionality Drone autonomously returns home Software
R15 Auto take off Control
R16 Auto landing Control
R17 Auto leveling (in flight) Drone is able to fly in heavy weather Does NOT require human action Control
R18 Minimal weight Drone uses carbon fiber materials Hardware
R19 Cargo capacity of 4 kg Drone is able to carry two catching devices Hardware
R20 Portability Drone is portable and easy to transport Does NOT hinder drone's robustness Hardware
R21 Fast deployment Drone can be deployed in under 5 minutes Does NOT hinder drone's robustness Hardware
R22 Minimal costs Drone cost is less than 800 euros Costs

UML Activity Diagram

Activity diagrams, along with use case and state machine diagrams describe what must happen in the system that is being modeled and therefore they are also called behavior diagrams. Since stakeholders have many issues to consider and manage, it is important to communicate what the overall system should do with clarity and map out process flows in a way that is easy to understand. For this, we will give an activity diagram of our system, including the overview of how the interceptor drone will work. By doing this, we hope to demonstrate the logic of our system and also model some of the software architecture elements such as methods, functions and the operation of the drone.

State of the Art

In this section the State of the Art (or SotA) concerning our project will be discussed.

Tracking/Targeting

To target a moving target from a moving drone, a way of tracking the target is needed. A lot of articles on how to do this, or related to this problem have been published:

  • Moving Target Classification and Tracking from Real-time Video. In this paper describes a way of extracting moving targets from a real-time video stream which can classify them into predefined categories. This is a useful technique which can be mounted to a ground station or to a drone and extract relevant data of the target.[6]
  • Target tracking using television-based bistatic radar. This article describes a way of detecting and tracking airborne targets from a ground based station using radar technology. In order to determine the location and estimate the target’s track, it uses the Doppler shift and bearing of target echoes. This allows for tracking and targeting drones from a large distance. [7]
  • Detecting, tracking, and localizing a moving quadcopter using two external cameras. In this paper a way of tracking and localizing a drone using the bilateral view of two external cameras is presented. This technique can be used to monitor a small airspace and detect and track intruders. [8]
  • Aerial Object Following Using Visual Fuzzy Servoing. In this article a technique is presented to track a 3D moving object from another UAV based on the color information from a video stream with limited info. The presented technique as presented is able to do following and pursuit, flying in formation, as well as indoor navigation. [9]
  • Patent for an interceptor drone tasked to the location of another tracked drone. This patent proposes a system which includes LIDAR detection sensors and dedicated tracking sensors. [10]
  • Patent for detecting, tracking and estimating the speed of vehicles from a moving platform. This patent proposes an algorithm operated by the on-board computing system of an unmanned aerial vehicle that is used to detect and track vehicles moving on a roadway. The algorithm is configured to detect and track the vehicles despite motion created by movement of the UAV.[11]
  • Patent for scanning environments and tracking unmanned aerial vehicles. This patent refers to systems and methods for scanning environments and tracking unmanned aerial vehicles within the scanned environments. It also provides a method for identifying points of interest in an image and generating a map of the region. [12]
  • Algorithms based on Multiplayer Differential Game Theory, such as two-player decomposition approach, maximum principle approach and minimum-time decomposition approach are presented, each arriving to an efficient way of intercepting an attacking UAV but focusing on optimizing a different variable based on the numbers of drones controlled and attacking the UAV. [13]

Autonomous flying

  • Patent for flight control using computer vision. This patent provides methods for computing a three-dimensional relative location of a target with respect to the reference aerial vehicle based on the image of the environment. [14]
  • Cooperative Control Method Algorithm. This paper presents experimental results for the simultaneous interception of targets by a team of UAV’s. It includes an overview of the co-operative control strategy which can also be used in this project’s drones. [15]
  • Framework for Autonomous On-board Navigation. This article presents a framework for independent autonomous flying of a drone solely based on its onboard sensors. In this framework, the high-level navigation, computer vision and control tasks are carried out in an external processing unit. [16]
  • Towards a navigation system for autonomous indoor flying. This article provides a framework for autonomous indoor flying for small UAV’s derived from existing systems for ground based robots. This system can be utilized for indoor drone interception where dodging objects and humans is one of the most important features. [17]
  • Mission path following for an autonomous unmanned airship. In this project (AURORA) multiple flight path following techniques through a set of pre-defined points are described and compared through simulation. The tests were conducted both with and without wind to show the performance of the controllers. [18]
  • Patent for autonomous tracking and surveillance. This patent refers to a method of protecting an asset by imposing a security perimeter around it which is further divided in a number of zones protected by unmanned aerial vehicles.[19]

Stopping drones

  • One way of catching a drone is by shooting at it with a net. Extensive research has been done on shooting nets, mainly for wildlife purposes [20][21]
  • Looking at drones shooting nets specifically, pneumatic launchers have been implemented successfully. [22]
  • Electromagnetic Launchers present another opportunity for launching a net to another drone. This article explains the mathematical model of such a system and shows the power of electromagnetic launchers, which offer very high acceleration speeds.[23]
  • This paper shows another option for shooting a net is using a hybrid pneumatic-electromagnetic launcher, giving the mathematical model of this system and simulation results. It shows that a hybrid system offers a huge control in the acceleration, more so than a simple pneumatic launcher or an electromagnetic one. [24]

General design of drones

  • Design and control of quadrotors with application to autonomous flying. This paper describes a design of a micro quadrotor, its simulation and linear and nonlinear control techniques. The techniques presented in this paper are broadly applicable and can be used in other drone environments, like drone interception activities. [25]
  • Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering. This article improves on previous work on aerodynamic effects impacting quadrotors. These are used to develop new control techniques that allow for more aggressive maneuvering. This is also useful in the pursuit of another agile drone or UAV. [26]

One big challenge surrounding drones is that their flight time is really limited. A way to prevent this and to have drones constantly surveilling the area they are programmed to is with autonomous mid-air battery swapping. [27]

Other

Although the use of drones for intervention is not directly military, this application can be seen as military. In a paper by Bradley Jay Strawser, the duty to employ UAV’s is discussed. It describes why there is nothing wrong in principle with using a UAV’s. [28]

There is also an existing company, in Delft, that is making drone intercepting drones called Delft Dynamics and they have built the DroneCatcher[29]

References

  1. Allianz Global Corporate & Specialty (2016). Rise of the Drones Managing the Unique Risks Associated with Unmanned Aircraft Systems
  2. Federal Aviation Administration (FAA) (2017). UAS Airborne Collision Severity Evaluation Air Traffic Organization, Washington, DC 20591
  3. From Wikipedia, the free encyclopedia (2018). Gatwick Airport drone incident Wikipedia
  4. Pamela Gregg (2018). Risk in the Sky? University of Dayton Research Institute
  5. From Wikipedia, the free encyclopedia (2019). Unmanned aerial vehicle Wikipedia
  6. A.J. Lipton, H.Fujiyoshi, R.S. Patil Moving target classification and tracking from real-time video (1998) Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201)
  7. P.F. Howland Target tracking using television-based bistatic radar (1999) IEE Proceedings - Radar, Sonar and Navigation Volume 146, Issue 3 p. 166 – 174
  8. M. Dreyer, S. Raj, S. Gururajan, J. Glowacki Detecting, Tracking, and Localizing a Moving Quadcopter Using Two External Cameras (2018) 2018 Flight Testing Conference, AIAA AVIATION Forum, (AIAA 2018-4281)
  9. O. Méndez, M. Ángel, M. Bernal, I. Fernando, C. Cervera, P. Alvarez, M. Alvarez, L. Luna, M. Luna, C. Viviana Aerial Object Following Using Visual Fuzzy Servoing (2011)
  10. Brian R. Van Voorst (2017). Intercept drone tasked to location of lidar tracked drone U.S. Patent No. US20170261604A1. Washington, DC: U.S. Patent and Trademark Office
  11. Eric Saund Christopher. Paulson Gregory. Burton Eric Peeters. (2014). System and method for detecting, tracking and estimating the speed of vehicles from a mobile platform U.S. Patent No. US20140336848A1. Washington, DC: U.S. Patent and Trademark Office
  12. Asa Hammond Nathan. Schuett Naimisaranya Das Busek. (2016). Scanning environments and tracking unmanned aerial vehicles U.S. Patent No. US20160292872A1. Washington, DC: U.S. Patent and Trademark Office
  13. Johan M. Reimann USING MULTIPLAYER DIFFERENTIAL GAME THEORY TO DERIVE EFFICIENT PURSUIT-EVASION STRATEGIES FOR UNMANNED AERIAL VEHICLES (2007) School of Electrical and Computer Engineering, Georgia Institute of Technology
  14. Guy Bar-Nahum. Hong-Bin Yoon. Karthik Govindaswamy. Hoang Anh Nguyen. (2018). Flight control using computer vision U.S. Patent No. US20190025858A1. Washington, DC: U.S. Patent and Trademark Office
  15. Timothy W. McLain and Randal W. Beard, Jed M. Kelsey Experimental Demonstration of Multiple Robot Cooperative Target Intercept (2007)
  16. J. J. Lugo, A. Zell Framework for Autonomous On-board Navigation with the AR.Drone (2013)
  17. S. Grzonka, G. Grisetti, W. Burgard Towards a navigation system for autonomous indoor flying(2009)
  18. J.R. Azinheira, E. Carneiro de Paiva, J.G. Ramos, S.S. Beuno Mission path following for an autonomous unmanned airship (2000)
  19. Kristen L. Kokkeby Robert P. Lutter Michael L. Munoz Frederick W. Cathey David J. Hilliard Trevor L. Olson (2008). System and methods for autonomous tracking and surveillance U.S. Patent No. US20100042269A1. Washington, DC: U.S. Patent and Trademark Office
  20. STEPHEN L. WEBB, JOHN S. LEWIS, DAVID G. HEWITT, MICKEY W. HELLICKSON, FRED C. BRYANT Assessing the Helicopter and Net Gun as a Capture Technique for White‐Tailed Deer (2008) The Journal of Wildlife Management Volume 72, Issue 1,
  21. Andrey Evgenievich Nazdratenko (2007) Net throwing device U.S. Patent No. US20100132580A1. Washington, DC: U.S. Patent and Trademark Office
  22. Mohammad Rastgaar Aagaah, Evandro M. Ficanha, Nina Mahmoudian (2016) Drone with pneumatic net launcher U.S. Patent No. US20170144756A1. Washington, DC: U.S. Patent and Trademark Office
  23. Leubner, Karel & Laga, Radim & Dolezel, Ivo. (2015) Advanced Model of Electromagnetic Launcher Advanced Model of Electromagnetic Launcher. Advances in Electrical and Electronic Engineering. 13. 223-229. 10.15598/aeee.v13i3.1419
  24. Domin, Jaroslaw & Kluszczyński, K. (2013) Hybrid pneumatic-electromagnetic launcher Hybrid pneumatic-electromagnetic launcher - general concept, mathematical model and results of simulation. 89. 21-25.
  25. S. Bouabdallah, R. Siegwart Design and control of quadrotors with application to autonomous flying (2007)
  26. H. Huang, G. M. Hoffmann, S. L. Waslander, C. J. Tomlin Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering (2009)
  27. Jacobsen, Reed; Ruhe, Nikolai; and Dornback, Nathan Autonomous UAV Battery Swapping (2018)
  28. Bradley Jay Strawser Moral Predators: The Duty to Employ Uninhabited Aerial Vehicles Journal of Military Ethics, Volume 9, 2010 – Issue 4
  29. Delft Dynamics DroneCatcher
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