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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.
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 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.
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.
Competency-oriented exams offer a wide range of advantages, especially where the use and mastery of third-party applications and tools play an important role. Therefore, we developed a competency-oriented setup for both our programming classes and exams ensuring their constructive alignment.
Exams were moved to the computer lab and designed to test both conceptional skills as well as the use of state-of-the-art programming tools. At the peak of the COVID-19 pandemic, when exams had to be moved from lab to online, we needed to design an online setup for our practical programming exams preserving the competency-oriented approach and its constructive alignment as well as the validity, reliability and fairness of the exams. The key was to use the same online tools that have been introduced
for running lectures and practical classes offering almost the same learning experience as before the pandemic. However, to ensure the validity and fairness of the exams, some kind of online supervision needed to be implemented as technical solutions were found to be either unusable or not working
properly in our case. This paper discusses the driving factors, the resulting technical and organizational setup as well as students’ feedback and lessons learned for further improvements. Therefore, COVID-19 has not been able to ruin our competency-oriented programming exams.
This paper describes a new concept and experiences of a distributed interdisciplinary learning programme for students across continents. The aim is to provide students with a truly Global Intercultural Project Experience (GIPE) by working together with peers from around the world, and solving real-life client’s problems. We have received seed-funding for four annual projects to engage students from Germany (Europe), Namibia (Africa), Indonesia (Asia), and Peru (Latin-America). In 2020, 30 students from four continents engaged in a one-semester distributed software development project for a Namibian client. Despite Covid-19 they successfully completed the project expressing deep appreciation for the learning opportunities overcoming challenges of working across wide-spread time zones, cultures, changing requirements, and various technical challenges. Considering the vast learning benefits, we suggest to incorporate such projects in all tertiary education curricula across the globe.
Air Handling units (AHU) are designed to guarantee a high indoor air quality for any time and outdoor condition all over the year. To do so, the AHU removes particle matter like dust or pollen and adapts the thermophysical properties of air to the desired, seasonal indoor comfort conditions. AHU have a robust design and thus operate for more than fifteen years, sometimes even for decades. An AHU designed today must consider and anticipate the change of user needs as well as outdoor air conditions for the next twenty years. To anticipate the outdoor air condition of coming decades, scientific models exist, which allow the design of peak performance and capacities of the air treatment components. It is most likely, that the ongoing climate change will lead to higher temperatures as well as higher humidity, while the comfort zone of human beings will remain at today’s values. Next to the impact of global warming with average rise of mean air temperature local effects will influence the operation of AHU. On effect investigated here is the steep temperature increase in city centres called urban heat islands. Heating and cooling capacities as well as water consumption for humidification are investigated for a reference AHU for fifteen regional locations in Germany. These regions represent all climate zones within the country. Additionally, the urban heat island effect was investigated for Berlin Alexanderplatz compared a rural area close by. The AHU was chosen to operate in an intensive care unit of a hospital. The set-up leads to 24/7 operation with 8760 hours per year. The article presents the modelling of current and future weather data as well as the unit set up. The calculated hourly performance and capacity parameters for current (reference year 2012) and future weather data (reference year 2045) yield energy consumption and peak loads of the unit for heating, cooling and humidification. The results are displayed by relative comparisons of each performance value.
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.