Informatik und Kommunikation
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Institute
Background: Priority during the SARS-CoV2 pandemic is that employees need to be protected from infection risks and business activities need to be ensured. New virus variants with increased infection risks require an evolved risk strategy.
Material and methods: Several standard measures such as testing, isolation and quarantine are com-bined to a novel risk strategy. Epidemiological model calculations and scientific knowledge about the course of SARS-CoV2 infectivity are used to optimize this strategy. The procedure is implemented in an easy-to-use calculator based on Excel.
Layout in practice and results: Alternative combinations of measures and practical aspects are dis-cussed. Example calculations are used to demonstrate the effect of the discussed measures.
Conclusion: That quarantine calculator derived from these principles enables even non-specialists to perform a differentiated risk analysis and to introduce optimized measures. Targeted testing routines and alternative measures ensure staff availability.
Autonomy and self-determination are fundamental aspects of living in our society. Supporting people for whom this freedom is limited due to physical impairments is the fundamental goal of this thesis. Especially for people who are paralyzed, even working at a desk job is often not feasible. Therefore, in this thesis a prototype of a robot assembly workstation was constructed that utilizes a modern Augmented Reality (AR)-Head-Mounted Display (HMD) to control a robotic arm. Through the use of object pose recognition, the objects in the working environment are detected and this information is used to display different visual cues at the robotic arm or in its vicinity. Providing the users with additional depth information and helping them determine object relations, which are often not easily discernible from a fixed perspective.
To achieve this a hands-free AR-based robot-control scheme was developed, which uses speech and head-movement for interaction. Additionally, multiple advanced visual cues were designed that utilize object pose detection for spatial-visual support. The pose recognition system is adapted from state-of-the-art research in computer vision to allow the detection of arbitrary objects with no regard for texture or shape.
Two evaluations were performed, a small user study that excluded the object recognition, which confirms the general usability of the system and gives an impression on its performance. The participants were able to perform difficult pick and place tasks with a high success rate. Secondly, a technical evaluation of the object recognition system was conducted, which revealed an adequate prediction precision, but is too unreliable for real-world scenarios as the prediction quality is highly variable and depends on object orientations and occlusion.
Venice 2018: Tradr Review
(2018)
The video shows an orthopoto and a textured 3D model of the location. 300 images were recorded in two short flights with a Mavic Pro in 50 meter height. The first one was a single grid while the camera facing down and the second one was a double grid facing the camera at an 60 degree angle. The 3D model is computed with OpenDroneMap.
In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with utomatically labeled images. Finally, we evaluate the performance of different neural networks.
The disruptive nature of the changing media landscape and technology-driven advances in communication have led to innovative ways of organizing work in the information and communication industry. This reorganization of work is reflected in the concept of New Work, which rethinks working concepts, styles, and employee behavior. Based on a survey among staff in the information and communication industry (n = 380), this study investigates the status quo of the implementation of New Work measures and their effectiveness in helping companies reach organizational goals. The results show that New Work measures are widely adopted although there is still unused potential. Moreover, the study demonstrates that the implementation of New Work measures supports companies in achieving New Work goals as well as overall organizational goals in the contexts of agile management, change management, internal communication, and evaluation.
The article highlights gender codes in design, particularly in web design, by means of current examples. Different aspects of gender-specific design are looked at in detail and their inherent problems discussed: on the one hand the development of a special solution (gender-specific for women), on the other hand, web design with reduced functionality and simplification of information (i.e. image representation) which sometimes even leads to a negation of technology. The article illustrates that gender codes and stereotypical role models can be embodied on different design levels of web design (use and artefact): in structure/navigation, in creative elements by the use of shape, colour and imagery and on a textual level. These design decisions have an impact on the power of users to act, their individual gender identity and the structural gender identity/social perception of gender. The article demonstrates that gender codes in current web design are very present and aims to sensitize the topic.
This Article introduces two research projects towards assistive robotic arms for people with severe body impairments. Both projects aim to develop new control and interaction designs to promote accessibility and a better performance for people with functional losses in all four extremities, e.g. due to quadriplegic or multiple sclerosis. The project MobILe concentrates on using a robotic arm as drinking aid and controlling it with smart glasses, eye-tracking and augmented reality. A user oriented development process with participatory methods were pursued which brought new knowledge about the life and care situation of the future target group and the requirements a robotic drinking aid needs to meet. As a consequence the new project DoF-Adaptiv follows an even more participatory approach, including the future target group, their family and professional caregivers from the beginning into decision making and development processes within the project. DoF-Adaptiv aims to simplify the control modalities of assistive robotic arms to enhance the usability of the robotic arm for activities of daily living. lo decide on exemplary activities, like eating or open a door, the future target group, their family and professional caregivers are included in the decision making process. Furthermore all relevant stakeholders will be included in the investigation of ethical, legal and social implications as well as the identification of potential risks. This article will show the importance of the participatory design for the development and research process in MobILe and DoF-Adaptiv.
This technical report is about the architecture and integration of very small commercial UAVs (< 40 cm diagonal) in indoor Search and Rescue missions. One UAV is manually controlled by only one single human operator delivering live video streams and image series for later 3D scene modelling and inspection. In order to assist the operator who has to simultaneously observe the environment and navigate through it we use multiple deep neural networks to provide guided autonomy, automatic object detection and classification and local 3D scene modelling. Our methods help to reduce the cognitive load of the operator. We describe a framework for quick integration of new methods from the field of Deep Learning, enabling for rapid evaluation in real scenarios, including the interaction of methods.
In the realm of digital situational awareness during disaster situations, accurate digital representations,
like 3D models, play an indispensable role. To ensure the
safety of rescue teams, robotic platforms are often deployed
to generate these models. In this paper, we introduce an
innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.
Recommendations for the Development of a Robotic Drinking and Eating Aid - An Ethnographic Study
(2021)
Being able to live independently and self-determined in one’s own home is a crucial factor or human dignity and preservation of self-worth. For people with severe physical impairments who cannot use their limbs for every day tasks, living in their own home is only possible with assistance from others. The inability to move arms and hands makes it hard to take care of oneself, e.g. drinking and eating independently. In this paper, we investigate how 15 participants with disabilities consume food and drinks. We report on interviews, participatory observations, and analyzed the aids they currently use. Based on our findings, we derive a set of recommendations that supports researchers and practitioners in designing future robotic drinking and eating aids for people with disabilities.
Random Forest Classification of Cognitive Impairment Using Digital Tree Drawing Test (dTDT) Data
(2024)
Early detection and diagnosis of dementia is a major challenge for medical research and practice. Hence, in the last decade, digital drawing tests became popular, showing sometimes even better performance than their paper-and-pencil versions. Combined with machine learning algorithms, these tests are used to differentiate between healthy people and people with mild cognitive impairment (MCI) or early Alzheimer’s disease (eAD), commonly using data from the Clock Drawing Test (CDT). In this investigation, a Random Forest Classification (RF) algorithm is trained on digital Tree Drawing Test (dTDT) data, containing socio-medical information and process data of 86 healthy people, 97 people with MCI, and 74 people with eAD. The results indicate that the binary classification works well for homogeneous groups, as demonstrated by a sensitivity of 0.85 and a specificity of 0.9 (AUC of 0.94). In contrast, the performance of both binary and multiclass classification degrades for groups with het erogeneous characteristics, which is reflected in a sensitivity of 0.91 and 0.29 and a specificity of 0.44 and 0.36 (AUC of 0.74 and 0.65), respectively. Nevertheless, as the early detection of cognitive impairment becomes increasingly important in healthcare, the results could be useful for models that aim for automatic identification
We investigate the possibility to use update propagation methods for optimizing the evaluation of continuous queries. Update propagation allows for the efficient determination of induced changes to derived relations resulting from an explicitly performed base table update. In order to simplify the computation process, we propose the propagation of updates with different degrees of granularity which corresponds to an incremental query evaluation with different levels of accuracy. We show how propagation rules for diferent update granularities can be systematically derived, combined and further optimized by using Magic Sets. This way, the costly evaluation of certain subqueries within a continuous query can be systematically circumvented allowing for cutting down on the number of pipelined tuples considerably.
Opportunities and Challenges in Mixed-Reality for an Inclusive Human-Robot Collaboration Environment
(2018)
This paper presents an approach to enhance robot control using Mixed-Reality. It highlights the opportunities and challenges in the interaction design to achieve a Human-Robot Collaborative environment. In fact, Human-Robot Collaboration is the perfect space for social inclusion. It enables people, who suffer severe physical impairments, to interact with the environment by providing them movement control of an external robotic arm. Now, when discussing about robot control it is important to reduce the visual-split that different input and output modalities carry. Therefore, Mixed-Reality is of particular interest when trying to ease communication between humans and robotic systems.
The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).
Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they “see” the world. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. All of these communicate cobot perception by visually indicating which objects in the cobot’s surrounding have been identified by their sensors. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. In a second remote experiment, we validated these findings with a broader non-specific user base. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. Overall, users prefer Line as a more straightforward visualization. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative.
Media Brand Management
(2022)
The management of media brands faces challenges. In order to be able to point out possible solutions, this article first explains the concept and the nature of “media brands.” Subsequently, various theoretical approaches to the explanation of media brands and their management are presented. Regardless of theoretical preferences, it is important to keep in mind the brand-strategic complexity of media management that is subsequently described. Due to their specificity, special attention is paid to the basic strategic positioning options and to the communication management of media brands. In this way, the special features of media brand management become clear in comparison with other products and services.
Media Brand Management
(2024)
Abstract
The management of media brands faces challenges. In order to be able to point out possible solutions, this article first explains the concept and the nature of “media brands.” Subsequently, various theoretical approaches to the explanation of media brands and their management are presented. Regardless of theoretical preferences, it is important to keep in mind the brand-strategic complexity of media management that is subsequently described. Due to their specificity,
special attention is paid to the basic strategic positioning options and to the communication management of media brands. In this way, the special features of media brand management become clear in comparison with other products and services.
Renewable and sustainable energy production by many small and distributed producers is revolutionizing the energy landscape as we know it. Consumers produce energy, making them to prosumers in the smart grid. The interaction between prosumers and other entities in the grid and the optimal utilization of new smart grid components (electric cars, freezers, solar panels, etc.) are crucial for the success of the smart grid. The Power Trading Agent Competition is an open simulation platform that allows researchers to conduct low risk studies in this new energy market. In this work we present Maxon16, an autonomous energy broker and champion of the 2016's Power Trading Agent Competition. We present the strategies the broker used in the final round and evaluate the effectiveness of the strategies by analyzing the tournament's results.
Abstract
Earthquakes, fire, and floods often cause structural collapses of buildings. However, the inspection of such damaged buildings poses a high risk for emergency forces or is even impossible. We present three recently selected missions of the Robotics Task Force of the German Rescue Robotics Center (DRZ), where both ground and aerial robots were used to explore destroyed buildings. We describe and reflect the missions as well as the lessons learned that have resulted from them. To make robots from research laboratories fit for real operations, realistic outdoor and indoor test environments were set up at the DRZ and used for tests in regular exercises by researchers and emergency forces. On the basis of this experience, the robots and their control software were significantly improved. Furthermore, expert teams of
researchers and first responders were formed, each with realistic assessments of the operational and practical suitability of robotic systems.
Journalism and Advertising: On the Separation of Editorial Content and Commercial Communication
(2024)
Abstract
The principle of separation between editorial content and commercial communication protects both the democratic and the commercial function of mass media. This article compiles all available statutory and professional regulations in Germany as an example of the various aspects of the principle of separation, such as the labeling obligation, the prohibition of paid content and tying transactions, as well as the handling of numerous forms of presentation of editorial advertising. Subsequently, the state of research is reported for the individual aspects of the principle of separation, in particular with regard to description and effect. Finally, proposed solutions for current application and desiderata are compiled.
This technical report is about the architecture and integration of commercial UAVs in Search and Rescue missions. We describe a framework that consists of heterogeneous UAVs, a UAV task planner, a bridge to the UAVs, an intelligent image hub, and a 3D point cloud generator. A first version of the framework was developed and tested in several training missions in the EU project TRADR.
Focusing on the implementation of the Smart Specialisation Strategy (S3), the chapter examines the development of cluster policies in the Ruhr Metropolis as a post-industrial region. The chapter traces the historical development of the Ruhr Area from its industrial peak in the 20th century to its slow transformation into a post-industrial landscape characterised by high urban density, new knowledge-based clusters and a persistent structural lack of effective regional cooperation. The analysis shows the conceptual shift from traditional cluster policies to the S3 approach, introduced by the European Union in 2014. The Smart Specialisation Strategy calls for a focus on comparative regional strengths and the involvement of a wide range of stakeholders in the identification of clusters for sustainable economic growth. The chapter also discusses the challenges and milestones in developing a coherent and effective Smart Specialisation Strategy, emphasising the need for inter-municipal cooperation and a new multi-level approach to regional governance. Using the case of the Ruhr Metropolis, the chapter highlights the opportunities and constraints of S3 policies to revitalise post-industrial regions by promoting innovation and adapting to global economic trends in cluster development, thus showing a way forward for other regions with similar structural challenges.
Problem
- How to effectively use aerial robots to support rescue forces?
- How to achieve good flight characteristics and long flight times?
- How to enable simple and intuitive control?
- How to efficiently record image data of the environment?
- How to generate flight and image data for rescue forces?
Implementation:
The flying robot was designed in Autodesk Fusion360. In order to achieve high stability as well as low weight, the frame was milled from carbon. Mounts such as for GPS and 360° camera were 3D printed. A special feature is that the flying robot is not visible in the panoramic view of the 360° camera. The flight controller of the robot was set up using Ardupilot. The communication with the robot is done via MAVLink (UDP).To support different platforms, a software was realized as a web application. The front end was created using HTML, CSS and Javascript.
The back end is based on Flask-Socket-IO (Python). For the intelligent recognition of motor vehicles a micro controller with an integrated camera is used. For the post-processing of flight and video data a pipeline was implemented for automation.
Introduction: Drawing tasks are an elementary component of psychological assessment in the evaluation of mental health. With the rise of digitalization not only in psychology but healthcare in general, digital drawing tools (dDTs) have also been developed for this purpose. This scoping review aims at summarizing the state of the art of dDTs available to assess mental health conditions in people above preschool age. Methods: PubMed, PsycInfo, PsycArticles, CINAHL, and Psychology and Behavioral Sciences Collection were searched for dDTs from 2000 onwards. The focus was on dDTs, which not only evaluate the final drawing, but also process data. Results: After applying the search and selection strategy, a total of 37 articles, comprising unique dDTs, remained for data extraction. Around 75 % of these articles were published after 2014 and most of them target adults (86.5 %). In addition, dDTs were mainly used in two areas: tremor detection and assessment of cognitive states, utilizing, for example, the Spiral Drawing Test and the Clock Drawing Test. Conclusion: Early detection of mental diseases is an increasingly important field in healthcare. Through the integration of digital and art based solutions, this area could expand into an interdisciplinary science. This review shows that the first steps in this direction have already been taken and that the possibilities for further research, e.g., on the optimized application of dDTs, are still open.
This technical report is about the mission and the experience gained during the reconnaissance of an industrial hall with hazardous substances after a major fire in Berlin. During this operation, only UAVs and cameras were used to obtain information about the site and the building. First, a geo-referenced 3D model of the building was created in order to plan the entry into the hall. Subsequently, the UAVs were used to fly in the heavily damaged interior and take pictures from inside of the hall. A 360° camera mounted under the UAV was used to collect images of the surrounding area especially from sections that were difficult to fly into. Since the collected data set contained similar images as well as blurred images, it was cleaned from non-optimal images using visual SLAM, bundle adjustment and blur detection so that a 3D model and overviews could be calculated. It was shown that the emergency services were not able to extract the necessary information from the 3D model. Therefore, an interactive panorama viewer with links to other 360° images was implemented where the links to the other images depends on the semi dense point cloud and located camera positions of the visual SLAM algorithm so that the emergency forces could view the surroundings.
Abstract
Indigenous people across the globe have all too often been marginalised and not been considered in decisions that directly concern their life. We maintain the significance of incorporating indigenous perspectives in society to create a global dialogue through direct participation. In this light we propose a situated action in which our co-author from the Ju/’hoansi tribe, one of the San ethnicity in Southern Africa, digitally records semi-structured conversations with members of other indigenous communities at the conference and public spaces in Sibu. Then participants are engaged into a participatory exploration of processing the audio files into sound installations and soundscapes which “amplify indigenous voices“. We anticipate that the products can be reused for further initiatives in the different countries, raising awareness and calling for action on matters of concern for indigenous people.
Abstract
In this paper we present the co-design and implementation of an extended reality escape room with 26 primary school students. The aim of our study was to explore the co-design process with students and to co-create a playable escape room, providing an asymmetric immersive experience in which players collaborate. We realised the complexity of designing such an escape room with primary students. We share our experiences and learnings in regard to required capacities and skills of co-designers, and adjustment of complexity and timing to players. We also maintain that the integration of extended reality technologies into escape rooms requires further research to realise asymmetric co-located collaboration.
Challenging visual localization of an UAV while flying out of a room into a snowy environment (~ 4:50). The UAV is equipped with a 360° camera. The localization is done with OpenVSLAM.
The video was recorded in Jan. 2019 at the Fire Brigade training center in Dortmund
To achieve nearly real time conditions the original resolution of 5k (30 fps) was reduced to 2k (ffmpeg -i video.mp4 -vf scale=1920:-1 -crf 25 vido-small.mp4) with high compression (-crf 25). This reduce the original size from 3.2 GB to 93MB (~ 4 MBit/s which could be transmitted online via a radio link). The localization shown did not use frameskip. With a frameskip above 1 the localization fails while the UAV is flying through the window. Indoor localization can be done with a frameskip of 3 in real time.
An EJB container can host three types of beans: Session beans to model business processes, entity beans to represent business objects and message-driven beans to provide for asynchronous method calls. This paper addresses entity beans and their mapping to persistent storage, especially relational and object-relational databases. A tool named BeanMaker is presented which can do object mapping either automatically by metadata analysis of a database schema or manually based on intrinsic real world semantics supplied by the user. BeanMaker is a running prototype system with an intuitive GUI interface. This paper looks what's behind the scenes and focuses on design issues and concepts of code generation.
The two churches, San Francesco and Sant'Agostino in Amatrice, Italy was hit by an earthquake on August 24 2016. Both churches are in a state of partial collapse, in need of shoring to prevent potential further destruction and to preserve the national heritage. The video show the mission at 1.Sept.2016 in clips of 10 seconds.
The TRADR project was asked by the Italian firebrigade Vigili del Fuoco to provide 3D textured models of two churches.
The team entered San Francesco with two UGVs (ground robots) and one UAV (drone, flown by Prof. Surmann), teleoperating them entirely out of line of sight and partially in collaboration. We entered Sant'Agostino with one UAV (also flown by Prof. Surmann) while two other UAVs were providing a view from different angles to facilitate maneuvering them entirely out of line of sight.
Robot arms are one of many assistive technologies used by people with motor impairments. Assistive robot arms can allow people to perform activities of daily living (ADL) involving grasping and manipulating objects in their environment without the assistance of caregivers. Suitable input devices (e.g., joysticks) mostly have two Degrees of Freedom (DoF), while most assistive robot arms have six or more. This results in time-consuming and cognitively demanding mode switches to change the mapping of DoFs to control the robot. One option to decrease the difficulty of controlling a high-DoF assistive robot arm using a low-DoF input device is to assign different combinations of movement-DoFs to the device’s input DoFs depending on the current situation (adaptive control). To explore this method of control, we designed two adaptive control methods for a realistic virtual 3D environment. We evaluated our methods against a commonly used non-adaptive control method that requires the user to switch controls manually. This was conducted in a simulated remote study that used Virtual Reality and involved 39 non-disabled participants. Our results show that the number of mode switches necessary to complete a simple pick-and-place task decreases significantl when using an adaptive control type. In contrast, the task completion time and workload stay the same. A thematic analysis of qualitative feedback of our participants suggests that a longer period of training could further improve the performance of adaptive control methods.
