Wie Serviceroboter dazu beitragen können, MitarbeiterInnen in Gesundheitseinrichtungen bei ihrer Arbeit zeitlich und körperlich zu entlasten — und damit die Arbeitsbedingungen zu verbessern.

Taking over arbitrary tasks like humans do with a mobile service robot in open-world settings requires a holistic scene perception for decision-making and high-level control. This paper presents a human-inspired scene perception model to minimize the gap between human and robotic capabilities. The approach takes over fundamental neuroscience concepts, such as a triplet perception split into recognition, knowledge representation, and knowledge interpretation. A recognition system splits the background and foreground to integrate exchangeable image-based object detectors and SLAM, a multi-layer knowledge base represents scene information in a hierarchical structure and offers interfaces for high-level control, and knowledge interpretation methods deploy spatio-temporal scene analysis and perceptual learning for self-adjustment. A single-setting ablation study is used to evaluate the impact of each component on the overall performance for a fetch-and-carry scenario in two simulated and one real-world environment.

Zusammenfassung Bedingt durch den eklatanten Personalmangel und den Druck, kosteneffizient arbeiten zu müssen, stehen Krankenhäuser vor großen Herausforderungen. Deshalb gerät Unterstützung durch mehr Automatisierung, wie sie in anderen Branchen bereits gang und gäbe ist, auch im Gesundheitssektor verstärkt in den Fokus. Während Serviceroboter im Operationssaal bereits etabliert sind, wurden in den letzten Jahren zahlreiche Roboter für weitere Einsatzfelder im Krankenhaus entwickelt. Das Kapitel stellt diese Einsatzfelder vor: patientenferne Routinetätigkeiten wie Transportdienste und Reinigung, Rehabilitation sowie schließlich Unterstützung in der Pflege. In kompakter Form werden ein kurzer Stand der Technik sowie ausgewählte Forschungstätigkeiten benannt. Es zeigt sich, dass die meisten am Markt verfügbaren Produkte auf eine ausgewählte Tätigkeit beschränkt sind und weitgehend fern der eigentlichen Pflegetätigkeit genutzt werden. Um weitere Produkte in die Praxis zu bringen, bedarf es neben den Forschungs- und Entwicklungstätigkeiten auch umfassender Tests der Roboter, damit sie sowohl ihren Nutzen, die Nutzerfreundlichkeit und Akzeptanz als auch das Potenzial für einen wirtschaftlichen Einsatz nachweisen können.

The rising number of elderly people and people in need of care results in an increased demand of new solutions to support self-initiative and independent living. Robotics and automation technologies have the potential to support and enhance the quality of our lives. This chapter analyzes the needs of persons with disabilities or age-related limitations and discusses possible tasks that new assistive service robots could support. It gives an overview of available products, selected research activities, and future challenges. Existing technologies can be grouped into two main categories: First, stand-alone devices, operated by the user explicitly or even operating (semi-)autonomously such as mobility aids, e.g., wheelchairs and rollators, manipulation aids, interaction platforms, or integrated mobile manipulators. Second, wearable devices that are physically connected with the user and operated implicitly by measuring their desired limb motion such as in orthoses, exoskeletons, or prostheses. Two developments are discussed as application examples: the robotic home assistant “Care-O-bot®” and the KONSENS-NHE exoskeleton for hand habilitation. An important future challenge in order to make robotic technologies available for everybody is to reduce their costs. On the technological side, user interfaces that allow teaching new tasks to assistive robots easily need to be designed. Finally, safe manipulation of assistive robots among humans must be guaranteed by new sensors and compliance with corresponding safety standards. For active orthoses and exoskeletons, challenges are the achievement of an adequate weight-to-benefit ratio and the design of reliable human-machine interfaces.

This study presents key technologies of a mobile service robot developed to manipulate objects around people safely. We demonstrate this ability to support staff in elderly care homes in the future. The take-over by a service robot allows the staff to spend less time with routine logistical tasks and therefore better focus on the interaction with residents. In the selected application scenario, the robot helps staff by (1) retrieving empty bottles from the residents' rooms, (2) bringing them to the kitchen, (3) taking the refilled bottles back to a table inside the residents' rooms. This task seems trivial for a person, but the robot needs to orchestrate numerous algorithms and components to work smoothly, such as bottle pose detection, manipulation, and navigation. A technical evaluation indicates a high performance of single components, but due to isolated failures, the overall scenario does not always succeed. Next to the technical aspects, it is fundamental to determine the acceptance of the robot, which was achieved by analyzing questionnaires given to care workers. Finally, this paper presents lessons learned to help other researchers in similar use-cases.

Coronavirus disease 2019 (COVID-19) has affected the conditions of work in healthcare institutions and the quality of patient care around the world. Emerging healthcare robotic technology may facilitate and improve the overall quality of life, as well as the diagnostics, rehabilitation, and intervention services. This paper reports the lessons learned from actions carried out in the implementation of the DIH-HERO project call across Europe for robotic solutions that support healthcare activities. Conclusion remarks are as follows: i) technology pull and the urgent need together accelerate the innovation development and deployment, ii) it takes time to establish safety and legal regulations for the deployment of human-machine devices, so the ethical, safety, and reliability aspects of robotic application need to be carefully considered, iii) technology adoption depends on the trust of the users to the technology, iv) existing robotic technology for prevention, diagnosis, hospital admission, rehabilitation, and intervention is mature enough for the adaptation and deployment, v) unskilled general population should be trained for the usage of robotic technology.

Germs can infect people with potentially dangerous diseases, possibly leading to the death of the patients or an reduction of their quality of life. Thus it is important to regularly disinfect potentially contaminated surfaces. But due to a labour shortage in the cleaning sector, this task is sometimes not done frequent enough. Service robots equipped with disinfection tools can assist in this task and help to overcome the shortage. But existing disinfection robots come with restrictions due to the undirected application of chemicals or UV-C light and a missing cleaning effect of these methods. To tackle these issues, we developed the mobile robot “DeKonBot” that cleans and disinfects specific surfaces often touched by humans (door handles, door knobs, light switches/buttons). The robot is based on the Scitos X3 platform from MetraLabs GmbH, with an UR5e arm from Universal Robots A/S and an additional cleaning tool consisting of two brushes. To detect the surfaces for cleaning, we designed and trained a CNN model and projected these detections onto collected 3D data to precisely localize the surface relative to the robot. By adapting previously defined motion templates for each surface type to the extracted dimensions, we can then completely clean and disinfect the current surface. During an experiment in a partner’s office building, we evaluated the performance of "DeKonBot" by cleaning a total of 45 objects (17 door handles, 12 door knobs and 16 light switches). Overall only one error due to perception occurred during this experiment. On average, the disinfection process took 214s for door handles, 173s for door knobs and 164s for light switches. After additional optimizations, it was possible to further reduce the execution time of the motions by 50s.

This paper presents a holistic scene perception approach that enhances the cognitive intelligence of professional cleaning robots to understand complex and dynamic environments. It builds upon a recently published CNN to detect and distinguish between dirt and objects on the floor. A multi-frame fusion of the detection results helps to increase the detection accuracy and provides semantic scene knowledge. Moreover, it enables the robot to perceive and avoid even small objects on the floor being barely detectable in the spatial sensor data. Lastly, the approach generates long-term dirt maps from scene knowledge to adjust the coverage strategy, e.g., to clean dirty areas more frequently. The integration of the holistic scene perception with state-of-the-art techniques for navigation, such as SLAM and coverage planning, and the deployment into a demonstrator, exemplifies the improvements on professional cleaning tasks.

The use of robotics in health care has seen a recent rise in interest due to its potential for use during the SARS-CoV-2 pandemic. The transmission rate of COVID-19 has meant that health-care workers are under increasing pressure, risks, and workload to manage the requirements of personal protective equipment, strict disinfection procedures, and the heightened medical needs of patients. Patients are suffering from isolation, and not just in hospitals: higher-risk individuals must shelter, meaning social interactions, particularly in care homes, are limited. Robots can help by providing disinfection and logistics services that support patients and health-care professionals, by acting as devices to be used for rehabilitation at home (for both pre-existing conditions and for COVID-19-related treatment), and via interventional systems that can widely distribute future vaccinations.

In the media more and more can be read about "care robots" as a possible solution for the current lack of qualified care staff but often without differentiating this term any further. This often leads to the assumption that robots are already able to take over physical care tasks with patients; however, current solutions primarily have assistive functions. The goal of this article is to elaborate for which application areas products already exist and which topics current research projects are dealing with based on concrete examples. On the one hand, assistive robots are presented that are designed to support staff in senior care institutions and hospitals. On the other hand, assistive robots are presented that support older persons or persons in need of care in their daily lives. These observations show that existing products either provide only reduced interaction capabilities or have only limited autonomy or "intelligence". Assistive robots providing more extensive, also physical interaction abilities and complex autonomous behavior are still a research topic.

This paper describes ongoing work on the development of a service robot for serving drinks to people sitting at tables, for example in the recreation room of a care-house. The robot, denoted the Tr ...

Field studies where robots are tested in real life settings bring different challenges for researchers, robotics scientists and users. In this paper, we address some of the challenges we encountered when testing two different drink serving service robots in the wild. We collect challenges from three different experiments. Two experiments were conducted in elderly care facilities, while a third experiment took place in the lobby of a concert hall. We focus on the challenges that researchers face during the preparation phase and the on-set deployment phase when testing robots in the wild. We point to potential difficulties that may arise and present some practical solutions to the issues encountered. Our results suggest that lab studies do not sufficiently prepare the researcher for research 'in the wild.'

In den Medien ist immer häufiger von dem Begriff „Pflegeroboter“ als mögliche Lösung für den aktuellen Pflegekräftemangel die Rede – jedoch oft, ohne diesen Begriff weiter zu differenzieren. Oft führt er zu der Annahme, Roboter wären bereits in der Lage, pflegerische Tätigkeiten am Menschen zu übernehmen, dabei geht es jedoch bei den meisten Robotern um assistierende Funktionen. Ziel dieses Beitrags ist es, anhand konkreter Bespiele darzustellen, für welche Anwendungen es bereits produktreife Roboterlösungen gibt, und womit sich aktuelle Forschungsprojekte beschäftigen. Dabei werden zum einen Assistenzroboter betrachtet, die der Unterstützung und Entlastung des Personals in Altenpflegeeinrichtungen und Krankenhäusern dienen, zum anderen werden Assistenzroboter vorgestellt, die ältere und pflegebedürftige Personen im Alltag unterstützen. Diese Betrachtungen zeigen, dass verfügbare Produkte entweder nur eingeschränkte Interaktionsfunktionen beinhalten oder über eine geringe Autonomie und „Intelligenz“ verfügen. Assistenzroboter mit umfangreicheren, auch physischen Interaktionsfähigkeiten und komplexem autonomem Verhalten sind noch der Forschung zuzuordnen.

We present a camera-based withdrawal detection system for inventory management on a robotic care cart. Navigating to the storage room for refilling the items takes time and energy for both robotic and manual care carts. Hence, tracking the inventory is crucial for efficiency. Currently, this task is performed by the nurses or care staff. Our approach aims at reducing the workload of the staff by warning them if the stock of an item is critically low. The extendable modular architecture combines different visual modalities such as hand tracking, rgb- and depth-based changes in drawer partitions and a motion cue, by fusing them for higher robustness. Our experimental results support the need for a detection system for such an application. Although the hand tracking modality provides the best accuracy among the other modalities, the fused result from different modalities outperforms regarding robustness.

One way to allow elderly people to stay longer in their homes is to use of service robots to support them with everyday tasks. Having this goal in mind, we design, develop, and evaluate a low-cost mobile robot to communicate with elderly people. The main idea is to create an affordable communication assistant robot which is optimized for multimodal Human-Robot Interaction (HRI). Our robot can navigate autonomously through dynamic environments using a new algorithm to calculate poses for approaching persons. The robot was tested in a real-life scenario in a residential care home for the elderly.

Assistance robots have a large potential to support patients and staff in outpatient and inpatient settings. Despite the need and large potential, the diffusion of robotic applications in the German healthcare sector is only slowly picking up pace. The objective of this study is to shed some light on the reasons and identify measures that support involved stakeholders in closing this gap in the upcoming years. Using an online survey, we addressed more than 150 clinics and nursing service providers throughout Germany with respect to the benefit of different robot application scenarios, drivers and barriers for the introduction of service robots in healthcare settings as well as estimated time savings. Concerning possible application areas, disinfection and cleaning robots are currently perceived to have the highest benefit, whereas the value of robots to support personal hygiene is considered rather low. The greatest drivers for using robot assistants in healthcare settings are their potential to save time for the staff as well as to increase employer attractiveness and higher efficiency in processes. The most frequently cited barriers are financing, data protection, legal obstacles and the importance of human contact. For three selected scenarios: assistance robots as guides, lifting robots and activation and communication robots, we further asked for the expected time savings. The results show differences between clinics as well as inpatient and outpatient nursing services. In order to accelerate the diffusion of robot assistants in Germany, several implications have to be considered: Acceptance and experience are positively correlated i.e. from a political standpoint, research programs are needed to support joint development of robot assistants by research, industry and end users. Legal and financial barriers should be reduced. For manufacturers, creating testing possibilities and close interaction with potential users for the identification of adequate scenarios and clarifying legal questions could prove to be beneficial in terms of a higher acceptance in the market.