UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters

We describe further progress towards the development of a MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking

Computer simulation of a pilot in V/STOL aircraft control loops

The objective was to develop a computerized adaptive pilot model for the computer model of the research aircraft, the Harrier II AV-8B V/STOL with special emphasis on propulsion control. In fact, two versions of the adaptive pilot are given. The first, simply called the Adaptive Control Model (ACM) of a pilot includes a parameter estimation algorithm for the parameters of the aircraft and an adaption scheme based on the root locus of the poles of the pilot controlled aircraft. The second, called the Optimal Control Model of the pilot (OCM), includes an adaption algorithm and an optimal control algorithm. These computer simulations were developed as a part of the ongoing research program in pilot model simulation supported by NASA Lewis from April 1, 1985 to August 30, 1986 under NASA Grant NAG 3-606 and from September 1, 1986 through November 30, 1988 under NASA Grant NAG 3-729. Once installed, these pilot models permitted the computer simulation of the pilot model to close all of the control loops normally closed by a pilot actually manipulating the control variables. The current version of this has permitted a baseline comparison of various qualitative and quantitative performance indices for propulsion control, the control loops and the work load on the pilot. Actual data for an aircraft flown by a human pilot furnished by NASA was compared to the outputs furnished by the computerized pilot and found to be favorable

Current and planned use of the Navstar Global Positioning System by NASA

NASA was quick to realize the potential that the Global Positioning System (GPS) had to offer for its many diverse vehicles, experiments and platforms. Soon after the first Block 1 GPS satellites were launched, NASA began to use the tremendous capabilities that they had to offer. Even with a partial GPS constellation in place, important results have been obtained about the shape, orientation and rotation of the earth and calibration of the ionosphere and troposphere. These calibrations enhance geophysical science and facilitate the navigation of interplanetary spacecraft. Some very important results have been obtained in the continuing NASA program for aircraft terminal area operations. Currently, a large amount of activity is being concentrated on real time kinematic carrier phase tracking which has the potential to revolutionize aircraft navigation. This year marks the launch of the first GPS receiver equipped earth-orbiting NASA spacecraft: the Extreme Ultraviolet Explorer and the Ocean Topography Experiment (TOPEX/Poseidon). This paper describes a cross section of GPS-based research at NASA

An analytical investigation of acquisition techniques and system integration studies for a radar aircraft guidance research facility, phase 2

A review of user requirements and updated instrumentation plans are presented for the aircraft tracking and guidance facility at NASA Wallops Station. User demand has increased as a result of new flight research programs; however, basic requirements remain the same as originally reported. Instrumentation plans remain essentially the same but with plans for up- and down-link telemetry more firm. With slippages in the laser acquisition schedule, added importance is placed on the FPS-16 radar as the primary tracking device until the laser is available. Limited simulation studies of a particular Kalman-type filter are also presented. These studies simulated the use of the filter in a helicopter guidance loop in a real-time mode. Disadvantages and limitations of this mode of operation are pointed out. Laser eyesafety calculations show that laser tracking of aircraft is readily feasible from the eyesafety viewpoint

Decentralized kalman filter approach for multi-sensor multi-target tracking problems

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Doğru pozisyon ve hedeflerin sayısı hava trafik kontrol ve füze savunması için çok önemli bilgilerdir. Bu çalışma, çoklu sensorlü çoklu hedef takibi sistemlerindeki veri füzyonu ve durum tahmini problemlerı için dağıtık Kalman Filtreleme Algoritması sunmaktadır. Problem, radar olarak her biri kendi veri işleme birimine sahip aktif sensörlerin hedef alanını gözlemlemesini esas almaktadır. Bu durumda her bir sistemin iz sayısı olacaktır. Çalışmada önerilen dağıtık Kalman Filtresi, başta füze sistemleri olmak üzere savunma sistemlerinde hareketli hedeflerin farklı sensörlerle izlerini kestirmek ve farklı hedefleri ayrıd etmek için kullanmaktır. Önerilen teknik, çoklu sensör sisteminden gelen verileri işleyen iki aşamalı veri işleme yaklaşımını içermektedir. İlk aşamada, her yerel işlemci kendi verilerini ve standart Kalman filtresi ise en iyi kestirimi yapmak için kullanılmaktadır. Sonraki aşamada bu kestirimler en iyi küresel bir kestirimi yapmak amacıyla dağıtık işlem modunda elde edilir. Bu çalışmada iki radar sistemi iki yerel Kalman filtresi ile uçakların pozisyonunu kestirmek amacıyla kullanılmakta, ardından bu kestirimler merkez işlemciye iletilmektedir. Merkez işlemci doğrulama maksadıyla bu bilgileri birleştirip küresel bir kestirim üretmektedir. Önerilen model uygulama olarak dört senaryo üzerinde test edildi. İlk senaryoda, tek bir hedef iki sensor tarafından izlenirken, ikincisinde, iki hedeften oluşan uzay herhangi bir sensor tarafından izlenmekte, üçüncüsünde, iki hedefin de herhangi bir sensor tarafından aynı anda izlenmesi, son olarak ise iki sensörden her birinin toplam üç hedeften herhangi ikisini izlediği senaryo göz önüne alınmıştır. Önerilen tekniğin performansı hata kovaryans matrisi kullanılarak değerlendirildi ve yüksek doğruluk ve optimal kestirim elde edildi. Uygulama sonuçları önerilen tekniğin yeteneğinin, yerel sensörlerce belirlenen ortak hedeflerin merkezi sistem tarafından ayırd edilebildiğini göstermiştir.For air traffic control and missile defense, the accurate position and the numbers of targets are the most important information needed. This thesis presents a decentralized kalman filtering algorithm (DKF) for data fusion and state estimation problems in multi-sensor multi-target tracking system. The problem arises when several sensors carry out surveillance over a certain area and each sensor has its own data processing system. In this situation, each system has a number of tracks. The DKF is used to estimate and separate the tracks from different sensors represent the targets, when the ability to track targets is essential in missile defense. The proposed technique is a two stage data processing technique which processes data from multi sensor system. In the first stage, each local processor uses its own data to make the best local estimation using standard kalman filter and then these estimations are then obtained in parallel processing mode to make best global estimation. In this work, two radar systems are used as sensors with two local Kalman filters to estimate the position of an aircraft and then they transmit these estimations to a central processor, which combines this information to produce a global estimation. The proposed model is tested on four scenarios, firstly, when there is one target and the two sensors are tracking the same target, secondly, when there are two targets and any sensor is tracking one of them, thirdly, when there are two targets and any sensor is tracking both of them and finally, when two sensors are used to track three targets and any sensor tracks any two of them. The performance of the proposed technique is evaluated using measures such as the error covariance matrix and it gave high accuracy and optimal estimation. The experimental results showed that the proposed method has the ability to separate the joint targets detected by the local sensors

A distributed architecture for unmanned aerial systems based on publish/subscribe messaging and simultaneous localisation and mapping (SLAM) testbed

A dissertation submitted in fulfilment for the degree of Master of Science. School of Computational and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa, November 2017The increased capabilities and lower cost of Micro Aerial Vehicles (MAVs) unveil big opportunities for a rapidly growing number of civilian and commercial applications. Some missions require direct control using a receiver in a point-to-point connection, involving one or very few MAVs. An alternative class of mission is remotely controlled, with the control of the drone automated to a certain extent using mission planning software and autopilot systems. For most emerging missions, there is a need for more autonomous, cooperative control of MAVs, as well as more complex data processing from sensors like cameras and laser scanners. In the last decade, this has given rise to an extensive research from both academia and industry. This research direction applies robotics and computer vision concepts to Unmanned Aerial Systems (UASs). However, UASs are often designed for specific hardware and software, thus providing limited integration, interoperability and re-usability across different missions. In addition, there are numerous open issues related to UAS command, control and communication(C3), and multi-MAVs. We argue and elaborate throughout this dissertation that some of the recent standardbased publish/subscribe communication protocols can solve many of these challenges and meet the non-functional requirements of MAV robotics applications. This dissertation assesses the MQTT, DDS and TCPROS protocols in a distributed architecture of a UAS control system and Ground Control Station software. While TCPROS has been the leading robotics communication transport for ROS applications, MQTT and DDS are lightweight enough to be used for data exchange between distributed systems of aerial robots. Furthermore, MQTT and DDS are based on industry standards to foster communication interoperability of “things”. Both protocols have been extensively presented to address many of today’s needs related to networks based on the internet of things (IoT). For example, MQTT has been used to exchange data with space probes, whereas DDS was employed for aerospace defence and applications of smart cities. We designed and implemented a distributed UAS architecture based on each publish/subscribe protocol TCPROS, MQTT and DDS. The proposed communication systems were tested with a vision-based Simultaneous Localisation and Mapping (SLAM) system involving three Parrot AR Drone2 MAVs. Within the context of this study, MQTT and DDS messaging frameworks serve the purpose of abstracting UAS complexity and heterogeneity. Additionally, these protocols are expected to provide low-latency communication and scale up to meet the requirements of real-time remote sensing applications. The most important contribution of this work is the implementation of a complete distributed communication architecture for multi-MAVs. Furthermore, we assess the viability of this architecture and benchmark the performance of the protocols in relation to an autonomous quadcopter navigation testbed composed of a SLAM algorithm, an extended Kalman filter and a PID controller.XL201