This master's thesis has been on modeling, identification and control of a hexarotor system. It has been carried out on behalf of UAS Europe in Link\"{o}ping. A set of non-linear dynamic equations describing the motion of the hexarotor were derived. These equations were then implemented in Matlab/Simulink, which became a good simulation environment for further studies. A decentralized control system using P-PD controllers was successfully implemented in both simulation and on a hexarotor platform. The non-linear simulation model and the hexarotor platform were then identified using black box identification between virtual controls and angular rates. The result from identification of the hexarotor platform was not bad at all, but left some room for improvements. These linear models ware then used to tune the parameters of the inner PD controllers using a method called placement of dominant poles. This method worked well in simulation environment but unfortunately not as well on the real platform.

The 2018 CPS-VO challenge is a competition focusing on the development of a drone which has the ability to search a area for a lost drone and recover it to a specific destination, all this is to be done autonomous. To participate in the challenge three thesis projects was done by three different teams. Those three projects combined created an autonomous hexacopter to compete with in the challenge. The thesis focuses on the development of a hexacopter with a gripping module which is to be used in the challenge. There are two main goals with the thesis. The first goal was to create a computer model of a hexacopter with a gripping module to be used in a simulation software called Gazebo. The simulation is controlled via Robot Operating System and is used as a basis for hardware development. The second goal was to use the results from the simulation to build a real hexacopter with a gripping module which can be used in the challenge. The hexacopter construction was based on own designs and all fabrication of parts for the gripping module was done using SolidWorks and 3D printers. The result became a hexacopter with a high thrust and a gripping module which can grab and hold on to recovered objects. The hexacopter was used during 2018 CPS-VO Challenge which was taking place in Arizona in May 2018.

Traditional quadcopter flight controllers use microcontrollers to run the code that keeps the drone in the air, and when more processing power or versatility is needed the same microcontrollers are used in tandem with Linux-based single-board computers. It would be cheaper and reduce complexity if the single-board computer could entirely replace the microcontrollers. We investigate whether it is possible to run a quadcopter using a Linux single-board computer as the flight controller, with no microcontrollers and otherwise the same hardware as used in hobby-grade quadcopters. We attempt to find out what the potential issues are and how to get around or mitigate them. To test it, a quadcopter will be built from hobby parts and the flight control software to be run on the flight controller will be developed. More specifically, the pulse-width modulation signals to the motor speed controllers are checked for stability and various methods of acquiring the radio control input in the form of pulse-width modulation signals are evaluated. The speed at which the flight control software is running is measured under different circumstances—with and without load and with and without mitigative measures active. We conclude that it was not possible to run a quadcopter using only the chosen Linux SBC as flight controller. The reason was because we could not accurately measure the radio control input, although there may be other additional issues. We did find that CPU time did not seem to be an issue even when an artificial stress was placed on the system, despite not being a real time system, and even less of an issue when the mitigation techniques discussed were applied.

In this thesis, black-box models describing the quadcopter system dynamics for attitude control have been estimated using closed-loop data. A quadcopter is a naturally unstable multiple input multiple output (MIMO) system and is therefore an interesting platform to test and evaluate ideas in system identification and control theory on. The estimated attitude models have been shown to explain the output signals well enough during simulations to properly tune a PID controller for outdoor flight purposes. With data collected in closed loop during outdoor flights, knowledge about the controller and IMU measurements, three decoupled models have been estimated for the angles and angular rates in roll, pitch and yaw. The models for roll and pitch have been forced to have the same model structure and orders since this reflects the geometry of the quadcopter. The models have been validated by simulating the closed-loop system where they could explain the output signals well. The estimated models have then been used to design attitude controllers to stabilize the quadcopter around the hovering state. Three PID controllers have been implemented on the quadcopter and evaluated in simulation before being tested during both indoor and outdoor flights. The controllers have been shown to stabilize the quadcopter with good reference tracking. However, the performance of the pitch controller could be improved further as there have been small oscillations present that may indicate a stronger correlation between the roll and pitch channels than assumed.

Die Auswahl an Hardware und Software auf dem Drohnen-Markt nimmt stetig zu. Autopilot-Software wie z. B. ArduCopter bietet bereits die Möglichkeit eine vor dem Flug definierte Liste von Wegpunkten automatisiert abzufliegen. Im Rahmen dieser Arbeit wird eine Software entwickelt, die dynamische Flugroutenplanung ermöglicht. Befindet sich beispielsweise ein Hindernis auf der aktuellen Flugbahn, berechnet ein Pfadplanungsalgorithmus eine neue Route ohne Kollision um dieses Hindernis herum.

No description available.

Now-a-days safety systems and their advanced features have become a major part of human lives. People are ready to pay accordingly for the features they get for and very enthusiastic towards technology and latest trends. One such thing is drone or multicopter. These days everybody is getting interested in drones to buy, not only the fact that it is used in various scientific ways, sports and recreation purposes but also the latest advancements that was taking place in the development of light weight flying vehicles has made many scientific researchers, multinational companies and almost all the people to turn their eye towards the development of drones. And many companies are doing research for development of new safety features which can be called as the safety for the future. Some companies already introduced drones into the market and are used in different ways for different purposes. The usage of this vehicles depends on how intelligently one uses these multicopters. This thesis introduces a feature that adds safety to the multicopters to prevent them from flying to no-fly-regions. The work in this thesis is done to provide an approach by the usage of Raspberry Pi 2 B for multicopter applications as the main development board. It also helps the multicopter to prevent entering the NFR by detecting the NFRs around them intelligently and avoid them so there shouldn\'t be any problem or damage for the multicopters. Here we use GPS sensor for getting the NMEA data as input to know the latitude and longitude positions and then transferred to RPI2 B which allows us to know the latitude and longitude positions and then transfer this data into database to store the data through a wireless medium i.e., Wi-Fi medium. Based on the information stored in database we can see the location in a graphical manner using the open street maps (OSM). After that different checks are performed to avoid the NFR : (i) We will check if the current point lies inside or outside the no-fly-region based on the map information of NFR using the Point in Polygon algorithm and then (ii) we are using some area based detection 4 algorithm to check the distance from the point to line using Paul Brouke algorithm to see how far is the next NFR from the current point and avoiding it and the information is updated and stored in the database accordingly .(iii) Later, if the multicopter is out of all no-fly-region then the distance to the next NFR or nearest ones is analyzed and the information will be used for safety purpose. By using geometry and algorithms we are checking and finding out the NFRs and avoid entering into the NFR space. If the point is detected inside a no-fly-region then the last point outside this region will be detected which is marked as safe and the multicopter will be backtracked to the previous point before entering the no-fly-region i.e., the safe point. This paper not only aims at multicopter safety but also throws light into the future systems that are going to be developed in the field of Car-2-X, ensuring extended safety of the passengers.

This master's thesis deals with the design of foldable propeller for UAVs. The design of the foldalble propeller is created based on theory of propellers and also on tha detail ana-lyzis of existing foldalble propellers with similar dimensions. The propeller is then manufac-tured and tested. One of the part of this thesis also describes design of central hub. At the end the methodical procedure of creating foldable propellers is suggested.

近年來多軸空拍機快速發展與普及，可預見其未來將成為新一代的輔助攝影工具。空拍機打破距離、角度的限制，讓時下流行的自拍（Selfie）照片相較於以往以手臂或自拍棒輔助的方式，拍出更具特色及多樣性的構圖。然而當前空拍機操作方式複雜，使用者需花費一定的練習時間才能熟練地控制空拍機至預定位置進行拍攝。 本研究針對空拍機的使用情境進行觀察，歸納傳統操作方式造成的問題，再依不同互動控制方法討論過往研究提出的解決方法之優勢與限制，並依據自拍行為之心智模型及過往研究經驗，設計兩階段互動流程：相機定位階段（Positioning）及鏡頭構圖階段（Framing），並在各階段中分別提出直接指向（Direct Pointing）、移動微調（Fine Tuning）及構圖調整（Framing）三種有別於傳統類比搖桿操控之互動模式。 本研究另設計一俱觸覺控制回饋、可單手操作之實體自拍遙控器，搭配前述互動設計實作兼具自動化移動及以使用者為中心進行操作之空拍機自拍互動控制系統原型Skyfie，並於戶外環境設計實驗場域進行使用者測試，測試使用者指揮空拍機至指定位置拍照之操作，評估互動流程中各操作方法之優劣。測試結果顯示Skyfie 互動控制系統相較於傳統的類比搖桿操控方式更易於學習及使用，且符合使用者對空間的認知，並依照回饋意見進行互動模式修正，以達成對空拍機初學者而言也簡單易學的互動操作方式。 / As personal drones become more popular, we can envision a future where flying selfie bots are always with us. Drones break the limits of distance and angle, providing more diversified composition than taking selfie with arms or a selfie stick. However, users have to be very skillful to pilot the drone and are not easy to take aerial selfies by state-of-the-art methods. Based on user observation and the mindset of selfie taking, we summarize the problems caused by the traditional control methods and generalize the interaction flow of selfie taking into two stages: Positioning and Framing stage. In each stage, we present new interaction techniques including a direct pointing technique, fine-tuning technique, and a touch manipulation for framing. We also present a selfie remote controller designed for single-hand operation to collocates with the interaction techniques, and implement a proof-of-concept Skyfie system for an outdoor user testing. The result shows users felt intuitive and expressed enthusiasm to take aerial selfies with our techniques. Finally, we discuss the insights from the evaluation and conclude with future directions.

This work deals with physical laws affecting behavior of a quadcopter as a mobile robot. It describes methods of controlling movements and stability. The result of the theoretical analysis is creation of simulation model. Moreover it depicts practical software developement of a real machine controller unit with its own conclusion, comparison between simulation and practical experiments and the workflow of the physical system construction.