PRE2018 3 Group9

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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


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]

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]


  • 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


We will now give more details about how we will approach this project. We will start our project by doing an extensive study of the current state of the problem. This will be achieved by studying the literature, recent reports from research institutes and the media and analysing patents which are strongly connected to our project. By doing this we hope to gather valuable insight into the issue of interceptor drones and see what are the current solutions for such a system.

Furthermore, we will continue to analyze the problem from a USE – user, society, enterprise – perspective. These three key areas 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. 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, together with a 3D model and list of parts necessary to build such a system. We would also like to develop a mobile application for tracking different parameters about the drones such as position and overall status. 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
  • Determine users and requirements
  • Consider multiple design strategies
  • Work on design (soft and hardware)
  • Work on prototype (soft and hardware)
  • Evaluate prototype


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.


  • 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


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 page Research hardware components 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 Research about the SotA Research building drones at scale Build UML diagram for software architecture Review wiki page
Write wiki introduction 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 a real drone prototype or 3D model Reviewing the Wiki and fixing spelling errors Finalise the Wiki Page Work on the final presantation
Write about the USE aspects Finalize the USE components Purchase or request the needed hardware Work on the code needed for the electronics Work on the layout of the Wiki Check on the relaisation of all objectives
Review the whole Wiki page Draw the schematics of electronics used Expand on the material on the Wiki more
Martijn Verhoeven Find 6 or more research papers Improve SotA Research hardware options Start on 3D model of drone Deliver 3D model of drone Review wiki page Finalise wiki page
Fill in draft planning Requirements Start thinking about electronics layout
Write about objectives USE analysis
Leo van der Zalm Find 6 or more research papers Proces feedback on objectives and prob. Proces feedback on state of. and put in on wiki Start working on drone prototype Make a bill of costs and list of parts Review wiki page Continue tasks from week 7 Finish all lose ends
Search information about subject Add finished obj. and prob. to wiki Research on the frame and looks of the drone Finish prototype Put in new devellopmets from week 3, 4 and 5 Write future developmetns Write conclusion/results part
Write problem statements Expand state of the art Research on different components of the drone Start looking at the final presentation
Write objectives
Group Work Introduction Expand on the requirements Research hardware components Interface design for the mobile app Drone prototype
Brainstorming ideas Expand on the state of the art Research different systems for stopping drones Start working on drone prototype Build 3d model of the drone
Find papers (5 per member) Society and enterprise needs Start working on 3d drone model Research into building a drone
User needs and user impacts Research into the costs involved
Define the USE aspects
Milestones Decide on research topic Add requirements to wiki page USE analysis finished Provide a bill of costs and list of parts
Add research papers to wiki page Add state of the art to wiki page
Write introduction for wiki page
Wiki page structure
Finish planning
Deliverables 3D drone model Mobile app prototype Final presentation
Wiki page


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.


The main user of the interception drone are going to be big organizations such as the government and large companies. Firstly, such drones would provide a huge utility to governments. As drone technology is advancing with huge steps, they have seen more and more use on governmental spying, with the intent of getting classified information on places where it is hard for men to reach. The implementation of such interception drones would mean that the government can secure itself from getting confidential information taken from other drones, operated by other people or governments with malicious purposes. Drones cannot only be programmed to spy but also, they can be used to execute deadly attacks on single targets or a group of people. It is important for governments to protect certain high importance personalities but also protect the people it represents, making interception drones a solution to this problem. But also in case of national security the government can benefit greatly from possessing interception drones. Think of terroristic attacks with drones. With the use of the interception the government does not have to risk human lives in order to take down the drone.

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.


Interception drones offer added security to the society. It prevents the capture of information by random drone users by intercepting these drones so that the private information can stay like that. It guarantees the members of the society that their information and security are being protected and it adds to the trust of the society in the government. One problem that occurs with the implementation of interception drones is that every drone, with malicious intent or not, can be a prey of the interception drone, discouraging the recreational use of drones.

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.


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 rouge 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

State of the Art

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


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]

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. [23]
  • 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. [24]

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. [25]


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. [26]

There is also an existing company, in Delft, that is making drone intercepting drones called Delft Dynamics and they have built the DroneCatcher[27]


  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
  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. S. Bouabdallah, R. Siegwart Design and control of quadrotors with application to autonomous flying (2007)
  24. H. Huang, G. M. Hoffmann, S. L. Waslander, C. J. Tomlin Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering (2009)
  25. Jacobsen, Reed; Ruhe, Nikolai; and Dornback, Nathan Autonomous UAV Battery Swapping (2018)
  26. Bradley Jay Strawser Moral Predators: The Duty to Employ Uninhabited Aerial Vehicles Journal of Military Ethics, Volume 9, 2010 – Issue 4
  27. Delft Dynamics DroneCatcher
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