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Self-supervised learning has proved to be a powerful approach to learn image representations without the need of large labeled datasets. For underwater robotics, it is of great interest to design computer vision algorithms to improve perception capabilities such as sonar image classification. Due to the confidential nature of sonar imaging and the difficulty to interpret sonar images, it is challenging to create public large labeled sonar datasets to train supervised learning algorithms. In this work, we investigate the potential of three self-supervised learning methods (RotNet, Denoising Autoencoders, and Jigsaw) to learn high-quality sonar image representation without the need of human labels. We present pre-training and transfer learning results on real-life sonar image datasets. Our results indicate that self-supervised pre-training yields classification performance comparable to supervised pre-training in a few-shot transfer learning setup across all three methods. Code and self-supervised pre-trained models are be available at https://github.com/agrija9/ssl-sonar-images
Die nachhaltige Organisation des Verkehrs soll auf kostengünstige, umweltfreundliche und nutzerfreundlichere Nahverkehrskonzepte, die möglichst viele Bürger zur Nutzung des ÖPNV einladen, abzielen. Vor diesem Hintergrund ist es das Ziel dieses Beitrags, instrumentelle Ansatzpunkte für ein Nachhaltigkeitscontrolling in ÖPNV-Unternehmen aufzuzeigen. Hierzu werden nachfolgend die Berücksichtigung der Nachhaltigkeit bei Investitionsentscheidungen, das Carbon Accounting (Transparenz über CO2-Emissionen), die Integration der ökologischen, ökonomischen und sozialen Nachhaltigkeitsdimension bei der Berichterstattung und die Einbindung der genannten Instrumente in ein Managementsystem skizziert. Die Nachhaltigkeitsdimensionen Ökologie, Ökonomie und Soziales lassen sich gut mit Hilfe mehrdimensionaler, integrierter Managementsysteme in der Organisation verankern und systematisch in interne Strukturen und Prozesse einbetten. Integrierte Managementsysteme können so eine wichtige Voraussetzung für ein effizientes Nachhaltigkeitscontrolling sein.
Das Roboter-Baukastensystem ProfiBot vom Fraunhofer Institut IAIS wird in Zusammenarbeit mit der Hochschule für Technik und Wirtschaft (HTW-Saarbrücken) und der Firma HighTec EDV-Systeme GmbH aus Saarbrücken zu einer mobilen Roboterplattform für die Ausbildung an Hochschulen weiterentwickelt. In dieser Diplomarbeit wird das vorgegebene eingebettete System und ein Echtzeitbetriebssystem der Firma HighTec EDV-Systeme GmbH benutzt, um die Regelung der Motoren und der Fahrzeugbewegungen zu implementieren. Ein Benutzer kann die mobile Roboterplattform mithilfe einer Schnittstelle zur Anwendungsprogrammierung (API) auf Basis von physikalischen Größen ansteuern und aktuelle Zustände abfragen. Um die mobile Roboterplattform flexibel benutzen zu können, werden mit einer zusätzlichen Elektronik digitale und analoge Ein- und Ausgänge des eingebetteten Systems auf die Anwendungen der Robotik angepasst. Neben einem Programmstartschalter und Status-LEDs können vier Schaltleisten zur Kollisionserkennung und analoge Sensoren mit Einheitssignal angeschlossen werden. Zuletzt wird die Reglerstruktur kalibriert und getestet.
Problem Fersenbeinfraktur
(2007)
Durch Dotierung eines nematischen Flüssigkristalles mit einer chiralen Substanz wird eine helikal strukturierte Phase induziert, die in der Lage ist, einfallendes Licht wellenlängenselektiv zu reflektieren. Bei der Reaktion des Dotiermittels mit einem gasförmigen Analyten verändern sich die Ganghöhe dieser Struktur und damit die reflektierte Wellenlänge. Liegt diese im Bereich des sichtbaren Lichts, ist eine Farbänderung mit dem menschlichen Auge zu beobachten. Es ist dabei sinnvoll den Flüssigkristall z.B. in einem Polymer einzukapseln, um ihn vor mechanischen Einflüssen und Umwelteinflüssen zu schützen. Eine Möglichkeit zur Einkapselung ist das koaxiale Elektrospinnen. Vorteile sind unter anderem die Realisierung einer großen Oberfläche und einer sehr geringen Wanddicke der schützenden Schale, die die Diffusion von Gasen durch die Wand hindurch ermöglicht. Um die Funktionsfähigkeit eines solchen Sensors zu testen, wurde ein CO2-sensitiver Flüssigkristall verwendet. Dieser wurde in eine Schale aus Polyvinylpyrrolidon (PVP) versponnen und die Reaktion mit CO2 spektroskopisch analysiert.
In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain.
In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.
In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain.
In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.
Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.
Robots applied in therapeutic scenarios, for instance in the therapy of individuals with Autism Spectrum Disorder, are sometimes used for imitation learning activities in which a person needs to repeat motions by the robot. To simplify the task of incorporating new types of motions that a robot can perform, it is desirable that the robot has the ability to learn motions by observing demonstrations from a human, such as a therapist. In this paper, we investigate an approach for acquiring motions from skeleton observations of a human, which are collected by a robot-centric RGB-D camera. Given a sequence of observations of various joints, the joint positions are mapped to match the configuration of a robot before being executed by a PID position controller. We evaluate the method, in particular the reproduction error, by performing a study with QTrobot in which the robot acquired different upper-body dance moves from multiple participants. The results indicate the method's overall feasibility, but also indicate that the reproduction quality is affected by noise in the skeleton observations.
The aim of this master thesis was to probe the view of Bonn’s citizens on the smart city project of the German city. A literature review helped defining the smart city term and identifying the smart city concept that is mostly used in Germany. This can be summarized as an urban planning concept using information and communication technology to build citizen centric, sustainable cities. According to this, a smart city should include transparent communication and participation of its citizens. The websites and different publications of Bonn were researched to understand its smart city strategy and vision. This revealed inconsistencies. To resolve these inconsistencies, three representatives of the city were inter-viewed. Based on the knowledge gained up to this point, two groups of Bonn’s inhabitants discussed the Smart City Bonn and presented their perception of it. With the help of this methodology, the following results were obtained. Communication and participation of the city are in many cases in line with the current recommendations for a smart city. Bonn has apparently recognized the relevance of these aspects in theory but should also implement them more consistently in practice. Currently the city council publishes contradictory information and does not plan to incorporate the sight of Bonn’s citizens to develop the smart city strat-egy in the first place, as it is recommended in common literature.
Evaluation and Optimization of IEEE802.11 multi-hop Backhaul Networks with Directional Antennas
(2020)
A major problem for rural areas is the inaccessibility to affordable broadband Internet connections. In these areas distances are large, and digging a cable into the ground is extremely expensive, considering the small number of potential customers at the end of that cable. This leads to a digital divide, where urban areas enjoy a high-quality service at low cost, while rural areas suffer from the reverse.
This work is dedicated to an alternative technical approach aiming to reduce the cost for Internet Service Provider in rural areas: WiFi-based Long Distance networks. A set of significant contributions of technology related aspects of WiFi-based Long Distance networks is described in three different fields: Propagation on long distance Wi-Fi links, MAC-layer scheduling and Interference modeling and Channel Assignment with directional antennas.
For each field, the author composes and discusses the state-of-the-art. Afterwards, the author derives research questions and tackles several open issues to develop these kinds of networks further towards a suitable technology for the backhaul segment.
This work describes extensions to the well-known Distributed Coordination Function (DCF) model to account for IEEE802.11n point-to-point links. The developed extensions cover adaptions to the throughput and delay estimation for this type of link as well peculiarities of hardware and implementations within the Linux Kernel. Instead of using simulations, the approach was extensively verified on real-world deployments at various link distances. Additionally, trials were conducted to optimize the CWmin values and the number of retries to maximize throughput and minimize delay. The results of this work can be used to estimate the properties of long-distance 802.11 links beforehand, allowing the network to be planned more accurately.
Urban LoRa networks promise to provide a cost-efficient and scalable communication backbone for smart cities. One core challenge in rolling out and operating these networks is radio network planning, i.e., precise predictions about possible new locations and their impact on network coverage. Path loss models aid in this task, but evaluating and comparing different models requires a sufficiently large set of high-quality received packet power samples. In this paper, we report on a corresponding large-scale measurement study covering an urban area of 200km2 over a period of 230 days using sensors deployed on garbage trucks, resulting in more than 112 thousand high-quality samples for received packet power. Using this data, we compare eleven previously proposed path loss models and additionally provide new coefficients for the Log-distance model. Our results reveal that the Log-distance model and other well-known empirical models such as Okumura or Winner+ provide reasonable estimations in an urban environment, and terrain based models such as ITM or ITWOM have no advantages. In addition, we derive estimations for the needed sample size in similar measurement campaigns. To stimulate further research in this direction, we make all our data publicly available.