TY - JOUR A1 - Gageik, Nils A1 - Strohmeier, Michael A1 - Montenegro, Sergio T1 - Waypoint flight parameter comparison of an autonomous UAV JF - International Journal of Artificial Intelligence & Applications (IJAIA) N2 - The present paper compares the effect of different waypoint parameters on the flight performance of a special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus influence the performance of the presented autonomous quadrocopter under real indoor navigation circumstances. Furthermore the paper demonstrates a drawback of the standard potential field method for navigation of such autonomous quadrocopters and points to an improvement. KW - autonomous UAV KW - Quadrocopter KW - Quadrotor KW - waypoint parameter KW - navigation Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96833 ER - TY - JOUR A1 - Strohmeier, Michael A1 - Walter, Thomas A1 - Rothe, Julian A1 - Montenegro, Sergio T1 - Ultra-wideband based pose estimation for small unmanned aerial vehicles JF - IEEE Access N2 - This paper proposes a 3-D local pose estimation system for a small Unmanned Aerial Vehicle (UAV) with a weight limit of 200 g and a very small footprint of 10 cm×10cm. The system is realized by fusing 3-D position estimations from an Ultra-Wide Band (UWB) transceiver network with Inertial Measurement Unit (IMU) sensor data and data from a barometric pressure sensor. The 3-D position from the UWB network is estimated using Multi-Dimensional Scaling (MDS) and range measurements between the transceivers. The range measurements are obtained using Double-Sided Two-Way Ranging (DS-TWR), thus eliminating the need for an additional clock synchronization mechanism. The sensor fusion is accomplished using a loosely coupled Extended Kalman Filter (EKF) architecture. Extensive evaluation of the proposed system shows that a position accuracy with a Root-Mean-Square Error (RMSE) of 0.20cm can be obtained. The orientation angle can be estimated with an RMSE of 1.93°. KW - UAV KW - navigation KW - pose estimation KW - distance measurement KW - DecaWave KW - extended Kalman filter KW - UWB Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177503 VL - 6 ER - TY - JOUR A1 - Kaiser, Dennis A1 - Lesch, Veronika A1 - Rothe, Julian A1 - Strohmeier, Michael A1 - Spieß, Florian A1 - Krupitzer, Christian A1 - Montenegro, Sergio A1 - Kounev, Samuel T1 - Towards Self-Aware Multirotor Formations JF - Computers N2 - In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios. KW - self-aware computing KW - unmanned aerial vehicles KW - multirotors KW - quadcopters KW - intelligent transportation systems Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-200572 SN - 2073-431X VL - 9 IS - 1 ER - TY - JOUR A1 - Werner, Lennart A1 - Strohmeier, Michael A1 - Rothe, Julian A1 - Montenegro, Sergio T1 - Thrust vector observation for force feedback-controlled UAVs JF - Drones N2 - This paper presents a novel approach to Thrust Vector Control (TVC) for small Unmanned Aerial Vehicles (UAVs). The difficulties associated with conventional feed-forward TVC are outlined, and a practical solution to conquer these challenges is derived. The solution relies on observing boom deformations that are created by different thrust vector directions and high-velocity air inflow. The paper describes the required measurement electronics as well as the implementation of a dedicated testbed that allows the evaluation of mid-flight force measurements. Wind-tunnel tests show that the presented method for active thrust vector determination is able to quantify the disturbances due to the incoming air flow. KW - unmanned aerial vehicles KW - thrust vector control KW - force feedback Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262153 SN - 2504-446X VL - 6 IS - 2 ER - TY - THES A1 - Strohmeier, Michael T1 - FARN – A Novel UAV Flight Controller for Highly Accurate and Reliable Navigation T1 - FARN – Eine neue UAV-Flugsteuerung für hochpräzise und zuverlässige Navigation N2 - This thesis describes the functional principle of FARN, a novel flight controller for Unmanned Aerial Vehicles (UAVs) designed for mission scenarios that require highly accurate and reliable navigation. The required precision is achieved by combining low-cost inertial sensors and Ultra-Wide Band (UWB) radio ranging with raw and carrier phase observations from the Global Navigation Satellite System (GNSS). The flight controller is developed within the scope of this work regarding the mission requirements of two research projects, and successfully applied under real conditions. FARN includes a GNSS compass that allows a precise heading estimation even in environments where the conventional heading estimation based on a magnetic compass is not reliable. The GNSS compass combines the raw observations of two GNSS receivers with FARN’s real-time capable attitude determination. Thus, especially the deployment of UAVs in Arctic environments within the project for ROBEX is possible despite the weak horizontal component of the Earth’s magnetic field. Additionally, FARN allows centimeter-accurate relative positioning of multiple UAVs in real-time. This enables precise flight maneuvers within a swarm, but also the execution of cooperative tasks in which several UAVs have a common goal or are physically coupled. A drone defense system based on two cooperative drones that act in a coordinated manner and carry a commonly suspended net to capture a potentially dangerous drone in mid-air was developed in conjunction with the project MIDRAS. Within this thesis, both theoretical and practical aspects are covered regarding UAV development with an emphasis on the fields of signal processing, guidance and control, electrical engineering, robotics, computer science, and programming of embedded systems. Furthermore, this work aims to provide a condensed reference for further research in the field of UAVs. The work describes and models the utilized UAV platform, the propulsion system, the electronic design, and the utilized sensors. After establishing mathematical conventions for attitude representation, the actual core of the flight controller, namely the embedded ego-motion estimation and the principle control architecture are outlined. Subsequently, based on basic GNSS navigation algorithms, advanced carrier phase-based methods and their coupling to the ego-motion estimation framework are derived. Additionally, various implementation details and optimization steps of the system are described. The system is successfully deployed and tested within the two projects. After a critical examination and evaluation of the developed system, existing limitations and possible improvements are outlined. N2 - Diese Arbeit beschreibt das Funktionsprinzip von FARN, einer neuartigen Flugsteuerung für unbemannte Luftfahrzeuge (UAVs), die für Missionsszenarien entwickelt wurde, die eine hochgenaue und zuverlässige Navigation erfordern. Die erforderliche Präzision wird erreicht, indem kostengünstige Inertialsensoren und Ultra-Breitband (UWB) basierte Funkreichweitenmessungen mit Roh- und Trägerphasenbeobachtungen des globalen Navigationssatellitensystems (GNSS) kombiniert werden. Die Flugsteuerung wird im Rahmen dieser Arbeit unter Berücksichtigung der Missionsanforderungen zweier Forschungsprojekte entwickelt und unter realen Bedingungen erfolgreich eingesetzt. FARN verfügt über einen GNSS-Kompass, der eine präzise Schätzung des Steuerkurses auch in Umgebungen erlaubt, in denen eine konventionelle Schätzung mit Hilfe eines Magnetkompasses nicht zuverlässig ist. Der GNSS-Kompass kombiniert die Messungen von zwei GNSS-Empfängern mit der echtzeitfähigen Lagebestimmung von FARN. Damit ist insbesondere der Einsatz von UAVs in arktischen Umgebungen im Rahmen des Projektes ROBEX trotz der schwachen horizontalen Komponente des Erdmagnetfeldes möglich. Zusätzlich erlaubt FARN eine zentimetergenaue relative Positionierung mehrerer UAVs in Echtzeit. Dies ermöglicht präzise Flugmanöver innerhalb eines Schwarms, aber auch die Ausführung kooperativer Aufgaben, bei denen mehrere UAVs ein gemeinsames Ziel haben oder physikalisch gekoppelt sind. In Verbindung mit dem Projekt MIDRAS wurde ein Drohnenabwehrsystem entwickelt, das auf zwei kooperativen Drohnen basiert, die koordiniert agieren und ein gemeinsam aufgehängtes Netz tragen, um eine potenziell gefährliche Drohne in der Luft einzufangen. Im Rahmen dieser Arbeit werden sowohl theoretische als auch praktische Aspekte der UAV-Entwicklung behandelt, wobei der Schwerpunkt auf den Bereichen der Signalverarbeitung, der Navigation und der Steuerung, der Elektrotechnik, der Robotik sowie der Informatik und der Programmierung eingebetteter Systeme liegt. Darüber hinaus soll diese Arbeit eine zusammengefasste Referenz für die weitere Drohnenforschung darstellen. Die Arbeit erläutert und modelliert die verwendete UAV-Plattform, das Antriebssystem, das elektronische Design und die eingesetzten Sensoren. Nach der Ausarbeitung mathematischer Konventionen zur Lagedarstellung, wird der eigentliche Kern des Flugreglers erläutert, nämlich die eingebettete Schätzung der Eigenbewegung und die prinzipielle Regelungsarchitektur. Anschließend werden, basierend auf grundlegenden Navigationsalgorithmen, fortgeschrittene trägerphasenbasierte Methoden und deren Zusammenhang mit der Schätzung der Eigenbewegung abgeleitet. Zusätzlich werden verschiedene Implementierungsdetails und Optimierungsschritte des Systems beschrieben. Das System wird innerhalb der beiden Projekte erfolgreich verwendet und getestet. Nach einer kritischen Untersuchung und Bewertung des entwickelten Systems werden bestehende Einschränkungen und mögliche Verbesserungen aufgezeigt. T3 - Research in Aerospace Information Technology - 1 KW - Drohne KW - Flugnavigation KW - Kalman-Filter KW - Phasenmehrdeutigkeit KW - Flugregelung KW - Unmanned Aerial Vehicle (UAV) KW - Sensorfusion KW - Error-State Extendend Kalman Filter KW - Baseline Constrained LAMBDA KW - Ultra-Wideband (UWB) radio ranging KW - Loose Coupling Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-223136 ER - TY - JOUR A1 - Strohmeier, Michael A1 - Montenegro, Sergio T1 - Coupled GPS/MEMS IMU Attitude Determination of Small UAVs with COTS JF - Electronics N2 - This paper proposes an attitude determination system for small Unmanned Aerial Vehicles (UAV) with a weight limit of 5 kg and a small footprint of 0.5m x 0.5 m. The system is realized by coupling single-frequency Global Positioning System (GPS) code and carrier-phase measurements with the data acquired from a Micro-Electro-Mechanical System (MEMS) Inertial Measurement Unit (IMU) using consumer-grade Components-Off-The-Shelf (COTS) only. The sensor fusion is accomplished using two Extended Kalman Filters (EKF) that are coupled by exchanging information about the currently estimated baseline. With a baseline of 48 cm, the static heading accuracy of the proposed system is comparable to the one of a commercial single-frequency GPS heading system with an accuracy of approximately 0.25°/m. Flight testing shows that the proposed system is able to obtain a reliable and stable GPS heading estimation without an aiding magnetometer. KW - Attitude Heading Reference System (AHRS) KW - magnetometer KW - MEMS IMU KW - Real-time Kinematics (RTK) KW - GPS KW - UAV KW - attitude determination Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-171179 VL - 6 IS - 1 ER - TY - JOUR A1 - Gageik, Nils A1 - Strohmeier, Michael A1 - Montenegro, Sergio T1 - An Autonomous UAV with an Optical Flow Sensor for Positioning and Navigation JF - International Journal of Advanced Robotic Systems N2 - A procedure to control all six DOF (degrees of freedom) of a UAV (unmanned aerial vehicle) without an external reference system and to enable fully autonomous flight is presented here. For 2D positioning the principle of optical flow is used. Together with the output of height estimation, fusing ultrasonic, infrared and inertial and pressure sensor data, the 3D position of the UAV can be computed, controlled and steered. All data processing is done on the UAV. An external computer with a pathway planning interface is for commanding purposes only. The presented system is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application. The focus of this paper is 2D positioning using an optical flow sensor. As a result of the performed evaluation, it can be concluded that for position hold, the standard deviation of the position error is 10cm and after landing the position error is about 30cm. KW - Autonomous UAV KW - Quadrocopter KW - Quadrotor KW - Optical Flow KW - positioning KW - navigation Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96368 ER -