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Institute
Quadrokopter sind Helikopter mit vier in einer Ebene angeordneten Rotoren. Kleine unbemannte Modelle, die oft nur eine Schubkraft von wenigen Newton erzeugen können, sind im Spielzeug- und Modellbaubereich beliebt, werden aber auch von Militär und Polizei als Drohne für Aufklärungs- und Überwachungsaufgaben eingesetzt. Diese Diplomarbeit befasst sich mit den theoretischen Grundlagen der Steuerung eines Quadrokopters und entwickelt darauf aufbauend eine kostengünstige Steuerplatine für einen Modellquadrokopter.
Die theoretischen Grundlagen enthalten eine Untersuchung der Dynamik eines frei fliegenden Quadrokopters, bei der Bewegungsgleichungen hergeleitet und mit den Ergebnissen verglichen werden, die in "Design and control of quadrotors with application to autonomous flying" ([Bou07]) vorgestellt wurden. Weiterhin wird die Funktionsweise verschiedener Sensoren beschrieben, die zur Bestimmung der aktuellen räumlichen Ausrichtung geeignet sind, und es werden Verfahren besprochen, mit denen die Ausrichtung aus den Messwerten dieser Sensoren abgeschätzt werden kann. Zusätzlich wird in den Schiefkörper der Quaternionen eingeführt, in dem dreidimensionale Rotationen kompakt dargestellt und effizient verkettet werden können.
Daran anschließend wird die Entwicklung einer einfachen Steuerplatine beschrieben, die sowohl einen autonomen Schwebeflug als auch Fernsteuerung ermöglicht. Die Platine wurde auf einem X-Ufo-Quadrokopter der Firma Silverlit entwickelt und getestet, der daher ebenfalls vorgestellt wird. Die eingesetzten Bauteile und deren Zusammenspiel werden besprochen. Dabei ist insbesondere die WiiMotionPlus hervorzuheben, die als kostengünstiges Gyrosensormodul verwendet wird. Daneben werden verschiedene Aspekte der Steuersoftware erläutert: die Auswertung der Sensordaten, die Zustandsschätzung mit Hilfe des expliziten komplementären Filters nach Mahony et al. ([MHP08]), die Umsetzung des Ausrichtungsreglers sowie die Erzeugung der Steuersignale für die Motoren. Sowohl die Steuersoftware als auch Schaltplan und Platinenlayout der Steuerplatine liegen dieser Arbeit auf einer CD bei. Schaltplan und Platinenlayout sind zusätzlich im Anhang der Arbeit abgedruckt.
3D-Curve-Skeletons are often used, because the object surface repesentation is less complex and also needs less computing power in further processing, compared to the representation created by the Medial Axis Transformation introduced 1967 by Harry Blum.
This theses aims at developing a 3D curve skelton approximation algorithm that keeps these advantages and is also able to handle different scenarios of the object surface input data.
The purpose of this bachelor- thesis is to teach Lisa - a robot of the university of Koblenz- AGAS department developed for participation in the @home league of the RoboCup - to draw. This requires the expansion of the robbie software framework and the operation of the robot- hardware components. Under consideration of a possible entry in the Open Challenge of the @home RoboCup, the goals are to detect a sheet of paper using Lisa- visual sensor, a Microsoft Kinect and draw on it using her Neuronics Katana robot arm. In addition, a pen mounting for the arm- gripper has to be constructed.
Outlined within this thesis are the procedures utilized to convert an image template into movement of the robotic arm, which in turn leads to drawing of a painting by the pen attached to the arm on a piece of paper detected by the visual sensor through image processing. Achieved were the parsing and drawing of an object made up of an indefinite amount of straight lines from a SVG-file onto a white sheet of paper, detected on a slightly darker surface and surrounded by various background objects or textures.
Pedestrian Detection in digital images is a task of huge importance for the development of automaticsystems and in improving the interaction of computer systems with their environment. The challenges such a system has to overcome are the high variance of the pedestrians to be recognized and the unstructured environment. For this thesis, a complete system for pedestrian detection was implemented according to a state of the art technique. A novel insight about precomputing the Color Self-Similarity accelerates the computations by a factor of four. The complete detection system is described and evaluated, and was published under an open source license.
The goal of this Bachelor thesis was programming an existig six-legged robot, which should be able to explore any environment and create a map of it autonomous. A laser scanner is to be integrated for cognition of this environment. To build the map and locate the robot a suitable SLAM(Simultaneous Localization and Mapping) technique will be connected to the sensor data. The map is reported to be the robots base of path planning and obstancle avoiding, what will be developed in the scope of the bachelor thesis, too. Therefore both GMapping and Hector SLAM will be implemented and tested.
An exploration algorithm is described in this bachelor thesis for exploring the robots environment. The implementation on the robot takes place in the space of ROS(Robot Operating System) framework on a "Raspberry Pi" miniature PC.
3D-models are getting more important in many areas such as multimedia applications, robotics or film industries. Of particular interest is the creation of 3D-models from a series of monocular images. This is because the cameras that are required for this purpose are becoming cheaper, smaller and more sophisticated at the same time. Increasingly often, suitable cameras are already integrated in devices like smartphones, tablet PCs or cars for example. Hence, there is a great potential for applications of this reconstruction technique.
This thesis is based on the use of a series of images that were taken with arncalibrated camera. The first step is to extract point correspondences from this image series making use of the well-known SURF- and A-KAZE-features. Starting from the point correspondences, it is possible to reconstruct a 3D-Modell with different algorithms that consists of a point cloud and camera poses. To reduce errors in the 3D-model, this thesis especially focuses on explaining the bundle adjustment algorithm, which is being used for a non-linear error minimization of a cost function.
The thesis also introduces the application for the 3D-reconstruction and the visualization of the results, that was developed in the course of this thesis.
The implemented system is evaluated based on statistics and the newly aquiredrnknowledge is presented. The thesis concludes with a summary of its results, and a number of ideas for potential future applications and developments.
Online Handschrifterkennung chinesischer Schriftzeichen auf androidfähigen mobilen Endgeräten
(2014)
Usage of mobile dictionaries or translators requires an input. This input has to be processed and recognized beforehand. Chinese characters are more suited for a handwritten input than a keyboard based one. Reason for that are the characters consisting mostly of pictograms or ideograms.
This thesis deals with an implementation of a prototypical recognition system on a mobile device. The recognition process should be online and therefore running while writing. It can save time for the user, because suggestions are made during runtime.
Basics and an overview over the current state of the art in online handwriting recognition will be given. An approach will be chosen and implemented, such that the recognition process is fast and needs little memory. The implementation will be tested and it will show, that a fast recognition can be possible on small devices. Suggestions for expansions and improvements will be given, including a future work part.
The goal of this work is evaluation and optimization of several eye-tracking algorithms for estimation of relevant features regarding accuracy. The extracted features are pupil- and glintcenters. The algorithms are applicable to off the shelf cameras. A synthetic model of the eye was modified and utilized. The model was used to supply ground truth for the evaluation of the methods.
In current research of the autonomous mobile robots, path planning is still a very important issue.
This master's thesis deals with various path planning algorithms for the navigation of such mobile systems. This is not only to determine a collision-free trajectory from one point to another. The path should still be optimal and comply with all vehicle-given constraints. Especially the autonomous driving in an unknown and dynamic environment poses a major challenge, because a closed-loop control is necessary and thus a certain dynamic of the planner is demanded.
In this paper, two types of algorithms are presented. First, the path planner, based on A*, which is a common graph search algorithm: A*, Anytime Repairing A*, Lifelong Planning A*, D* Lite, Field D*, hybrid A*. Second, the algorithms which are based on the probabilistic planning algorithm Rapidly-exploring Random Tree (Rapidly-exploring Random Tree, RRT*, Lifelong Planning RRT*), as well as some extensions and heuristics. In addition, methods for collision avoidance and path smoothing are presented. Finally, these different algorithms are evaluated and compared with each other.