MDU, in collaboration with several other universities, plans to join the World Robotic Sailing Championship (WRSC), where in certain sub-challenges some object detection is necessary. Such as for detecting objects such as boats, buoys, and possibly other items. Utilizing a camera system could significantly aid in these tasks, and in this research, an omnidirectional camera is proposed. This is a camera that offers a wide field of view of 360 degrees and could provide comprehensive information about the boat’s surroundings. However, these images use a spherical camera model, which projects the image on a sphere and, when saved to a 2D format, becomes very distorted. To be able to use state-of-the-art vision algorithms for object detection and tracking, this research proposes to project these images to other formats. As such, four systems using object detection and tracking are made that uses different image representation projected from the spherical images. One system uses spherical images and is used as a baseline, while the three remaining systems use some form of projection. The first is cubemap projection, which projects the spherical image to a cube and unfolds this image on a 2D plane. The two other image representations used perspective projections, which are when the spherical image is projected to small sub-images. The two image representations that used perspective projections had 4 and 8 perspective images. None of the systems ultimately performed very well but did have some advantages and disadvantages.

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Artificial intelligence and machine learning have seen great progress in recent years. In this work, we will look at the application of machine learning in visual navigational systems for unmanned vehicles in natural environments. Previous works have focused on navigational systems with deep convolutional neural networks (CNNs) for unmanned aerial vehicles (UAVs). In this work, we evaluate the robustness and applicability of these methods for unmanned ground vehicles (UGVs). To evaluate the robustness and applicability of this machine learning approach for UGV two experiments where performed. In the first, data from Swiss trails and photos collected in Swedish forests where used to train deep CNNs. Several models are trained using data collected in different environments at different heights. By cross evaluating the trained models on the other datasets the impact of changing camera position and switching environment can be evaluated. In the second experiment, a navigational system using the trained CNN models were constructed. By evaluating the ability of the system to autonomously follow a forest path an understanding of the applicability of these methods for UGVs in general can be obtained. There where several results from the experiments. When comparing models trained on different datasets, we could see that the environment has an effect on the performance of the navigation, but even more so, the approach is sensitive to the camera position. Finally, an online test to evaluate the applicability of this approach as an end-to-end navigation system for UGVs is done. This experiment showed that these methods, on their own, are not a viable option for an end-to-end navigational system for UGVs in forest environments. / Artificiell intelligens och maskininlärning har gjort stora framsteg de senaste åren. I detta arbete tittar vi på tillämpningen av maskininlärning i visuella navigationssystem för obemannade fordon i naturliga miljöer. Tidigare verk har fokuserat på navigeringssystem med djupa ``convolutional neural networks'' (CNNs) för obemannade luftfarkoster. I detta arbete, utvärderar vi hur pass applicerbara och robusta dessa metoder är som navigationssystem för obemannade markfordon (UGVs). För att utvärdera hur pass applicerbara och robusta dessa maskininlärningsmetoder är för UGVs så utfördes två experiment. I det första experimentet utvärderas hur systemet reagerar på nya miljöer och kamerapositioner. Ett redan existerande dataset, med med foton från stigar i de schweiziska alperna, kompletterade med två nya dataset. Dessa två nya samlingar består av foton från svenska skogsstigar insamlade på två olika höjder. Dessa tre olika dataset användes för att träna tre olika olika modeller. Genom att korsutvärdera de tränade modellerna på de olika dataseten kan effekten av att förändrad kameraposition samt att byta miljö utvärderas. I det andra experimentet utrustades en UGV med ett navigationssystem byggt på dessa tränade modeller. Genom att utvärdering hur pass autonomt denna UGV kan följa en skogsstig så ges en förståelse för hur pass applicerbara dessa metoder är för UGVs generellt. Experimentet gav flera resultat. Korsutvärderingen visade att dessa metoder är känsliga för både kameraposition och miljö. Där byte av kameraposition har en större negativ påverkan på navigationsresultatet, än byte av miljö. Slutligen visade ett online-test att dessa metoder, i sin naiva form, inte är ett lämpligt alternativ för navigationssystem för UGVs i skogsmiljöer.

Path planning that takes kinodynamic constraints into account is a crucial part of critical missions where autonomous vehicles must function independently without communication from an operator as this ensures that the vehicle will be able to follow the planned path. In this thesis, an algorithm is presented that can plan kinodynamically feasible paths through large scale continuous costmap environments for different constraints on the maximum allowed acceleration and jerk along the path. The algorithm begins by taking a small stochastic sample of the costmap, with a higher probability to keep more information from the cheaper, interesting areas of the map. This random sample is turned into a graph to which Dijkstra's algorithm is applied in order to obtain an initial guess of a path. Simulated annealing is then used to first smooth this initial guess to obey the kinodynamic constraints and then optimize the path with respect to cost while keeping the kinodynamics below the set limits. The majority of the simulated annealing iterations utilize a GPU to significantly reduce the computational time needed. The performance of the algorithm was evaluated by studying the paths generated from a large number of different start and end points in a complex continuous costmap with a high resolution of 2551×2216 pixels. To evaluate the robustness of the algorithm a large number of paths were generated, both with the same and with different start and end points, and the paths were inspected both visually, and the spread of the cost of the different paths was studied.  It was concluded that the algorithm is able to generate paths of high quality for different limits on the allowed acceleration and jerk as well as achieving a low spread in cost when generating multiple paths between the same pair of points. The utilization of a GPU to improve computational performance proved successful as the GPU executed between 2.4 and 2.8 times more simulated annealing iterations in a given time compared to the CPU. This result hopefully inspires future work to utilize GPUs to improve computational performance, even in problems that traditionally are solved using sequential algorithms.

The need to further unlock productivity of forestry operations urges the increase of forestry automation. Many essential operations in forest production, such as harvesting, forwarding, planting, etc., have the potential to be automated and obtain benefits such as improved production efficiency, reduced operating costs, and an improved working environment. In view of the fact that forestry operations are performed in forest environments, the automation of forestry operations is thus complex and extremely challenging. To build the ability of forest machine automation, it is necessary to construct an environmental cognitive ability of the forest machine as basis. Through a combination of exteroceptive sensors and algorithms, forest machine vision can be realized. Using new and off-the-shelf solutions for detecting, locating, classifying and analyzing the status of objects of concern surrounding the machine during forestry operations in combination with smart judgement and control, forest operations can be automated. This thesis focuses on the introduction of vision systems on an unmanned forest platform, aiming to create the foundation for autonomous decision-making and execution in forestry operations. Initially, the vision system is designed to work on an unmanned forest machine platform, to create necessary conditions to either assist operators or to realize automatic operation as a further step. In this thesis, vision systems based on stereo camera sensing are designed and deployed on an unmanned forest machine platform and the functions of detection, localization and pose estimation of objects that surround the machine are developed and evaluated. These mainly include a positioning function for forest terrain obstacles such as stones and stumps based on stereo camera data and deep learning, and a localization and pose estimation function for ground logs based on stereo camera and deep learning with added functionality of color difference comparison. By testing these systems’ performance in realistic scenarios, this thesis describe the feasibility of improving the automation level of forest machine operation by building a vision system. In addition, the thesis also demonstrate that the accuracy of stump detection can be improved without significantly increasing the processing load by introducing depth information into training and execution.

Dieser Beitrag zeigt ein umgesetztes Gesamtkonzept für eine manuelle und kollisionsfreie Telemanipulation von Industrierobotern basierend auf einem digitalen Zwilling. Als Demonstrator dient hierfür ein Aufbau, mit dem eine manuelle Pick-and-Place-Applikation exemplarisch nachgebildet wird. Der manuell gesteuerte Industrieroboter soll kleine, mit Flüssigkeit befüllten Glasfläschchen (sogenannten Vials) aufnehmen, transportieren und an einen definierten Ablageort kollisionsfrei absetzten. In diesem Beitrag werden sämtliche notwendigen Schritte nachvollziehbar dargestellt und erläutert. Die Definition und Realisierung des digitalen Zwillings, die Gestaltungsmöglichkeiten des Arbeitsraums und dessen Überwachung sowie die Kollisionsüberprüfung sollen hierbei die Schwerpunkte darstellen. Außerdem werden die notwendigen Systemvoraussetzungen Umsetzung des Konzepts dargestellt. Die eigentliche Bewegungssteuerung des Industrieroboters wird mit unterschiedlichen Manipulatoren verifiziert.

Seit jeher üben Roboter eine Faszination auf den Menschen aus. Es ist die Ähnlichkeit zum Menschen, die technische Systeme, die mit einer höheren Intelligenz ausgestattet sind, gleichermaßen faszinierend wie erschreckend erscheinen lässt. Der Gedanke daran, technische Kreaturen zu erschaffen, die uns erhabenen menschlichen Wesen „das Wasser reichen“ oder uns gar übertreffen können, lässt uns nicht mehr los. Die Erkenntnis von dem Nutzen, den uns derartige Wesen in allen denkbaren Bereichen bringen könnten, mündet jedoch sehr schnell in eine Skepsis im Hinblick auf eine Entmündigung und Entwertung des Menschen. Denn schon heute, obgleich die Forschung in vielen Bereichen noch in den Kinderschuhen steckt, geraten wir in zahlreichen Lebensbereichen in Kontakt mit technischen Systemen, die eine starke Wirkung auf uns ausüben und viele grundlegende Fragen aufwerfen. Die Arbeit widmet sich der ethischen Dimension autonomer (Pflege-)Systeme und thematisiert zu diesem Zweck konkrete Anwendungsszenarien. Dabei geht es nicht um allgemeine ethische Fragen, sondern konkret um den Aspekt der Vereinbarkeit autonomer technischer Systeme mit der Menschenwürde ihrer Nutzer. Auch der Gesichtspunkt des Einflusses von autonomen technischen Innovationen auf das Selbstverständnis des Menschen (Menschenbild) ist Teil der Arbeit. Als Maßstab für moderne technische Entwicklungen dient der Würdegrundsatz aufgrund seiner enormen Bedeutung für das Recht sowie für das zugrundeliegende und allgemeine Menschenbild. Im Rahmen einer an einem humanistischen Weltbild orientierten Gesellschaft steht die Menschenwürde als oberster Wert, dem moralische und rechtliche Entwicklungen gerecht werden müssen, über allem. Daher gilt es, moderne Entwicklungen immer auch im Hinblick auf ihre Vereinbarkeit mit der Menschenwürde zu überprüfen. So lässt sich feststellen, ob ein Regulierungsbedarf besteht und wie Regulierungen im Einzelnen auszugestalten sind. Gleichzeitig muss aber auch die Menschenwürde gesellschaftlichen Entwicklungen gerecht werden. Demgemäß wird sie vom Bundesverfassungsgericht als Grundsatz, der sich aktuellen Herausforderungen stellt und zur Erzwingung eines gesellschaftlichen Diskurses führt, angesehen. Die hiesige Arbeit soll einen Beitrag zu der bereits angestoßenen gesellschaftlichen Debatte rund um den technischen Fortschritt und konkret um die Probleme, die mit der zunehmenden Autonomie technischer Systeme einhergehen, leisten. / Robots have always fascinated people. It is the similarity to humans that makes technical systems equipped with a higher intelligence seem both fascinating and frightening. The thought of creating technical creatures that can "hold a candle" to us sublime human beings, or even surpass us, never leaves us. However, the realization of the benefits that such beings could bring us in all conceivable areas quickly leads to scepticism with regard to the incapacitation and devaluation of humans. Even today, although research in many areas is still in its infancy, we come into contact with technical systems in numerous areas of life that have a strong effect on us and raise many fundamental questions. The thesis is dedicated to the ethical aspects of autonomous (care) systems and addresses specific application scenarios and their ethical implications. This thesis is less about general ethical questions, but rather attempts to analyse their compatibility with user dignity. This includes the influence of autonomous technical innovations on the self-image of man. The principle of dignity serves as a standard for modern technical developments, due to its significant importance in law and the underlying and general view of man‘s self-image. In the context of a society based on a humanistic worldview, human dignity stands above all else, serving as the highest value that moral and legal developments must do justice to. It is, therefore, paramount to always examine modern developments with regards to human dignity. This makes it possible to determine whether there is a need for regulation and how regulations should be designed in detail. Simultaneously, human dignity must also reflect social developments. Accordingly, it is viewed by the (German) Federal Constitutional Court as a principle that addresses current challenges and promotes the enforcement of social discourse. This thesis intends to contribute to the ongoing social debate around technical progress and, specifically, the problems associated with the increasing autonomy of technical systems. After examining the concept of technical autonomy and its manifestations, human dignity is reviewed contextually. The Federal Constitutional Court's concept of human dignity was chosen for this purpose, being particularly suitable for examining specific application scenarios of autonomous technical systems. The reasons for this are explained in detail within the thesis. The self-image of man is closely linked to the principle of human dignity. A reflection on this and in particular the question of the compatibility of this term with modern developments is therefore inevitable. In the course of introductory explanations, the events that contributed to relationships between people and technical systems / robots, thus, making human dignity violations possible in the first place, are described. A detailed presentation of technical autonomy scenarios and their review against select dignity concepts further explores where violations of human dignity become relevant. The identification of possible dignity violations is carried out using technical systems in the care sector, as the focus here is particularly human-centric, given that the definition of humanity itself, is or should be the de facto guiding principle for care measures. Simply put, this human-centric area allows for a particularly clear representation of all aspects that are relevant to violations of human dignity. Lastly, the thesis concludes with a discussion of how violations of human dignity can be avoided in the future. Options for defusing conflicts with human dignity are provided and discussed. The thesis finally ends with an overall summary of the findings, research perspectives, and an outlook.

In diesem Beitrag wird die IDEA-Box MC (Industrial Digitalization in Education of Automation – Motion Control) und die damit realisierbaren Anwendungsmöglichkeiten und vermittelbaren Lerninhalte vorgestellt. Neben dem mechanischen Aufbau werden die unterschiedlichen Möglichkeiten und Methoden im Bereich der Positioniertechnik von mechatronischen Systemen, die sich heutzutage mit speicherprogrammierbaren Steuerungen realisieren lassen, vorgestellt. Dabei werden neben einfachen Rast-in-Rast Bewegungen von Einzelachsen, vor allem das resonanzfreie Positionieren von schwingungsfähigen Systemen und synchronisierten Mehrachssystemen im Kurvenscheibenverbund (integrierte und synchronisierte Robotik) aufgezeigt und beschrieben. Außerdem wird aufgeführt, dass mithilfe eines digitalen Zwillings kollisionsfreie Telemanipulation realisiert werden kann.

Being able to accurately measure distances in depth images is important for accurately reconstructing objects. But the measurement of depth is a noisy process and depth sensors could use additional correction even after factory calibration. We regard the pair of depth sensor and image sensor to be one single unit, returning complete 3D information. The 3D information is combined by relying on the more accurate image sensor for everything except the depth measurement. We present a new linear method of correcting depth distortion, using an empirical model based around the constraint of only modifying depth data, while keeping planes planar. The depth distortion model is implemented and tested on the Intel RealSense SR300 camera. The results show that the model is viable and generally decreases depth measurement errors after calibrating, with an average improvement in the 50 percent range on the tested data sets. / Att noggrant kunna mäta avstånd i djupbilder är viktigt för att kunna göra bra rekonstruktioner av objekt. Men denna mätprocess är brusig och dagens djupsensorer tjänar på ytterligare korrektion efter fabrikskalibrering. Vi betraktar paret av en djupsensor och en bildsensor som en enda enhet som returnerar komplett 3D information. 3D informationen byggs upp från de två sensorerna genom att lita på den mer precisa bildsensorn för allt förutom djupmätningen. Vi presenterar en ny linjär metod för att korrigera djupdistorsion med hjälp av en empirisk modell, baserad kring att enbart förändra djupdatan medan plana ytor behålls plana. Djupdistortionsmodellen implementerades och testades på kameratypen Intel RealSense SR300. Resultaten visar att modellen fungerar och i regel minskar mätfelet i djupled efter kalibrering, med en genomsnittlig förbättring kring 50 procent för de testade dataseten.

The navigation tasks in advanced home robotic applications incorporating reliable revisiting strategies are dependent on very low cost but nevertheless rather accurate localization systems. In this paper a localization system based on the principle of trilateration is described. The proposed system uses only a single small base station, but achieves accuracies comparable to systems using spread beacons and it performs sufficiently for map building. Thus it is a standalone system and needs no odometry or other auxiliary sensors. Furthermore a new approach for the problem of the reliably detection of areas without direct line of sight is presented. The described system is very low cost and it is designed for use in indoor service robotics. The paper gives an overview on the system concept and special design solutions and proves the possible performances with experimental results.