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This paper presents an approach towards a mobile learning environment, which is flexible in terms of supported scenarios, supported devices and input channels. The approach makes use of existing and commonly used channels like SMS, Twitter or Face book to increase acceptance and ease-of-use of mobile devices in learning scenarios. Envisaged application scenarios are described along with technical details for their realization.
The first robots are currently appearing on the consumer market. Initially they are targeted at rather simple applications such as entertainment and home convenience. For more complex areas, these robots will need to collaborate and interactively communicate with their human users, which requires appropriate man-machine interaction technologies and considerable cognitive abilities on the robot's side. Consumer acceptance will strongly depend on the integrated system. Thus, system integration and evaluation of the integrated system is becoming increasingly important. This paper describes our approach to construct a robotic assistance system. We present experience with an integrated technology demonstration and exposure of the integrated system to the public.
Bipolar electrosurgical systems are used for the treatment of benign prostatic hyperplasia (BPH) in urology. In order to analyse electrothermal processes during surgery the power loss density distribution around a bipolar resectoscope is calculated out of the measured potential distribution in isotonic saline solution ex situ. During further analysis power loss density values act as input for the Penne's bioheat equation. To achieve results, which are as realistic as possible, a method to obtain power loss density values, depending on the observed tissue or medium in the operating field, is presented. Applying this method, the power loss density distribution in isotonic saline solution at 25 °C is compared to the distribution calculated for the average conductivity of biological tissue in the region of interest.
In this contribution we present a novel approach to transform data from time-of-flight (ToF) sensors to be interpretable by Convolutional Neural Networks (CNNs). As ToF data tends to be overly noisy depending on various factors such as illumination, reflection coefficient and distance, the need for a robust algorithmic approach becomes evident. By spanning a three-dimensional grid of fixed size around each point cloud we are able to transform three-dimensional input to become processable by CNNs. This simple and effective neighborhood-preserving methodology demonstrates that CNNs are indeed able to extract the relevant information and learn a set of filters, enabling them to differentiate a complex set of ten different gestures obtained from 20 different individuals and containing 600.000 samples overall. Our 20-fold cross-validation shows the generalization performance of the network, achieving an accuracy of up to 98.5% on validation sets comprising 20.000 data samples. The real-time applicability of our system is demonstrated via an interactive validation on an infotainment system running with up to 40fps on an iPad in the vehicle interior.
Untersuchung des Einflusses von Längsrissen in Drähten auf die Impedanz eines Wirbelstromsensors
(2012)
Influencing Parameters on Measuring the Cross-Section Area of Hot Rolled Rods in Steel Industries
(2014)
Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach
(2009)
The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. In dynamic environments, where trajectories are evolving online, this is not a trivial task. The dynamical systems approach to robotics provides a framework for robust incorporation of fluctuating sensor information, but control of movement time is usually restricted to rhythmic motion and realized through stable limit cycles. The present work uses a Hopf oscillator to produce discrete motion and formulates an online adaptation rule to stabilize total movement time against a wide range of disturbances. This is integrated into a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion as an example. The approach is demonstrated on a Khepera mobile unit in order to show its reliability even when depending on low-level sensor information.
Recognition of emotions from multimodal cues is of basic interest for the design of many adaptive interfaces in human-machine interaction (HMI) in general and human-robot interaction (HRI) in particular. It provides a means to incorporate non-verbal feedback in the course of interaction. Humans express their emotional and affective state rather unconsciously exploiting their different natural communication modalities such as body language, facial expression and prosodic intonation. In order to achieve applicability in realistic HRI settings, we develop person-independent affective models. In this paper, we present a study on multimodal recognition of emotions from such auditive and visual cues for interaction interfaces. We recognize six classes of basic emotions plus the neutral one of talking persons. The focus hereby lies on the simultaneous online visual and accoustic analysis of speaking faces. A probabilistic decision level fusion scheme based on Bayesian networks is applied to draw benefit of the complementary information from both – the acoustic and the visual – cues. We compare the performance of our state of the art recognition systems for separate modalities to the improved results after applying our fusion scheme on both DaFEx database and a real-life data that captured directly from robot. We furthermore discuss the results with regard to the theoretical background and future applications.
To reduce the number of traffic accidents and to increase the drivers comfort, the thought of designing driver assistance systems arose in the past years. Fully or partly autonomously guided vehicles, particularly for road traffic, pose high demands on the development of reliable algorithms. Principal problems are caused by having a moving observer in predominantly natural environments. At the Institut fur Neuroinformatik methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a solution for a driver assistance system. We concentrate on the aspects of video-based scene analysis and organization of behavior.
Relevance & Research Question: Smartphones have become an integrated part in everyday life facilitating communication, information access, entertainment and organization anytime and anywhere. However, the omnipresence of such devices can evoke psychological dependencies and the need of being always connected resulting in discomfort when the smartphone is not accessible. While few studies have found heightened anxiety during smartphone absence (e.g. Cheever, Rosen, Carrier, & Chavez, 2014), such research is scarce. Therefore, we aimed at expanding existing research asking whether the mere imagination of smartphone absence suffices to trigger anxiety and affect user’s context evaluations.
Immer mehr ältere Menschen leben von ihren Angehörigen getrennt und können über Kommunikationsmedien wie Telefon und Skype nur eingeschränkt gemeinsame Erlebnisse erzeugen. In diesem Paper wird die technische Umsetzung eines Konzeptes vorgestellt, das es Familienmitgliedern ermöglicht über das Internet gemeinsam „Mensch-ärgere-dich-nicht“ zu spielen. Durch Videotelefonie und eine besondere Anordnung der Hardware werden die Spieler trotz räumlicher Trennung virtuell an einen Tisch gebracht und dadurch ein gemeinsames Erlebnis erzeugt. Die Clientanwendung wird dabei als plattformunabhängiger Webservice und die Videotelefonie mittels verschiedener Standards und Server realisiert.
In this paper we discuss how group processes can be influenced by designing specific tools in computer supported collaborative leaning. We present the design of a shared workspace application for co-constructive tasks that is enriched by certain functions that are able to track, analyze and feed back parameters of collaboration to group members. Thereby our interdisciplinary approach is mainly based on an integrative methodology for analyzing collaboration behavior and patterns in an implicit manner combined with explicit surveyed data of group members’ attitudes and its immediate feedback to the groups. In an exploratory study we examined the influence of this feedback function. Although we could only analyze ad-hoc groups in this study, we detected some benefits of our methodology which might enrich real life Learning Communities’ collaboration processes. The data analysis in our study showed advantages of this feedback on processes of a group’s well-being as well as parameters of participation. These results provide a basis for further empirical work on problem solving groups that are supported by means of parallel interaction analysis as well as its re-use as information resource.
This paper describes an educational application that combines handhelds (PDAs) and programmable Lego bricks in a classroom scenario that deals with the problem of letting a robot escape from a maze. It is specific to our setting that the problem can be solved both in the physical world by steering a Lego robot and in a simulated software environment on a PDA or on a PC. This approach enables the students to generate successful sets of rules in the simulation and to test these sets of rules later in physical mazes, or to create new types of mazes as challenges for known rule sets. In this paper we describe the technical setting for this scenario, different pedagogical scenarios and we will report an evaluation with a group of students in a school environment.
The paper provides a contextualization process to adapt Open Knowledge Resources for the need of public administrations. By help of a matching strategy, culture and context profiles of learners and learning resources are compared. The comparison allows to draw inferences how to contextualize an open knowledge resource for own learning needs. An example is illustrated and future research fields are proposed.
Der Bedarf an feuerverzinkten Stahlbändern ist besonders in der Automobilindustrie sehr groß und es werden zugleich immer höhere Qualitäten gefordert. Hierbei bildet vor allem die Homogenität der Zinkschichtdicke ein entscheidendes Qualitätsmerkmal. Um das Stahlband ausreichend vor Umwelteinflüssen zu schützen, muss eine, vom Kunden spezifizierte, Mindestzinkschichtdicke aufgetragen werden. Beim hier angewandten Verzinkungsverfahren durchläuft das Band ein Zinkbad und anschließend wird das überschüssige Zink berührungs-los mittels sogenannten Abblasdüse so abgetragen, sodass eine möglichst homogene Zinkschicht erhalten bleibt. Hierzu ist es notwendig den Abstand zwischen Band und Airknife konstant zu halten. Störende Bandbewegungen führen zu inhomogene Zinkschichtdicken, welche die Qualität der Verzinkung vermindern. Diese Qualitätsverminderung und der erhöhte Zinkeinsatz soll durch geeignete Maßnahmen verringert werden. Bisher eingesetzte berührungslose Bandstabilisatoren können die Bandbewegung im Allge-meinen dämpfen, jedoch treten noch Betriebszustände auf, in denen eine inhomogene Zinkschicht sichtbar ist. Die Ursache dieser Inhomogenitäten liegt in anlagenbedingten dominanten Schwingungen des Bandes, deren Ursache zu klären ist. Im vorliegenden Beitrag wird ein Modell der Bandbewegung vorgestellt, das durch die theore-tische Modellbildung und experimentelle Identifikation erstellt worden ist. Das Modell beschreibt die Bewegung des Bandes bezüglich ausgewählter Freiheitsgrade und ermöglicht die Analyse der kritischen Betriebszustände. Darüber hinaus soll dieses Modell zur Stabilisierung des Bandes in einer modellgestützten Reglung verwendet werden.
Fahrerassistenzsysteme werden eingesetzt, um dem Fahrer
eines Kraftfahrzeugs Handlungsabläufe abzunehmen. Diese Handlungsabläufe
werden definiert durch eine Aufgabenstellung, die vom Fahrer an das Fahrerassi-
stenzsystem übergeben oder systembedingt gelöst wird. Bei komplexen Fahreras-
sistenzsystemen ist an eine autonome Navigation im Straßenverkehr gedacht. Es
wird ein neues Verfahren vorgestellt, welches eine Bewegungssteuerung eines
autonomen Fahrzeugs durchführen kann. Es werden der Lenkwinkel und die Ge-
schwindigkeit beeinflußt. Für diese Aufgabe wird ein dynamischer Ansatz aus
dem Bereich der neuronalen Felder gewählt. Relevante Attribute für den Fahrt-
verlauf auf unterschiedlichem Abstraktionsniveau können dabei einfach (additiv)
verarbeitet werden.
We describe the general concept, system architecture, hardware, and the behavioral abilities of Cora (Cooperative Robot Assistant, see Fig. 1), an autonomous non mobile robot assistant. Outgoing from our basic assumption that the behavior to perform determines the internal and external structure of the behaving system, we have designed Cora anthropomorphic to allow for humanlike behavioral strategies in solving complex tasks. Although Cora was built as a prototype of a service robot system to assist a human partner in industrial assembly tasks, we will show that Cora’s behavioral abilities are also conferrable in a household environment. After the description of the hardware platform and the basic concepts of our approach, we present some experimental results by means of an assembly task.