This literature review presents a comprehensive analysis of the use and potential application scenarios of collaborative robots in the industrial working world, focusing on their impact on human work, safety, and health in the context of Industry 4.0. The aim is to provide a holistic evaluation of the employment of collaborative robots in the current and future working world, which is being increasingly driven by the automation and digitization of production processes, and which can be outlined using the term Work 4.0. In this context, the forms of work organization, and the demands and impacts on humans are changing profoundly. Collaborative robots represent a key technology to aid the transition. The review utilizes expert interviews for identifying relevant keywords, and follows the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) framework to evaluate peer-reviewed literature between 2002 and January 2022. The analysis includes forms of interaction, and the distribution of roles, control interfaces, safety procedures, and ergonomics and health. In addition, the review offers a heatmap displaying the research topics of 715 publications for each year, and a database of these publications in BibTeX format that is publicly accessible. The review highlights the challenges, potential benefits, and trends of using collaborative robots in the industrial working world, emphasizing the importance of a careful evaluation of their impact on human work, safety, and health. It offers a tool set for researchers and practitioners to further explore and evaluate the employment of collaborative robots in Work 4.0.

Previous algorithms for slicing, path planning or trajectory planning of additive manufacturing cannot be used consistently for multidirectional additive manufacturing with pure object manipulation in wire-arc additive manufacturing. This work presents a novel path planning approach that directly takes robot kinematics into account and thus ensures the reachability of all critical path poses. In an additional step, the planned path segments are smoothed so that joint velocity limits are respected. It is shown that the implemented path planner generates executable robot paths and at the same time maintains the process quality (in this case, sufficient coverage of the slice area). While the introduced method enables the generation of reachable printing paths, the smoothing algorithm allows for the execution of the path with respect to the robot’s velocity limits and at the same time improves the slice coverage. Future experiments will show the realization of the real robot setup presented.

While human–robot collaboration is already integrated in industrial and service robotics applications, it is only used with able-bodied workers. However, collaboration through assistive robots is a major driver toward the inclusion of people with disabilities, which was demonstrated in recent research projects. Currently, inclusive robot workplaces have to be customized toward the work process and the individual needs of the person. Within, robots act along a fixed schedule and are not able to adapt to changes within the process or the needs of the interacting person. Hence, such workplaces are expensive and unappealing for companies of the first labor market, and do not realize the full potential of the technology. In this work, we propose a generalized approach toward the inclusion of people with disabilities with collaborative robots. To this end, we propose a system that analyzes the in situ capabilities of a person using a two-stage reasoning approach. The methodology is based on an ontology that allows the matchmaking of individual capabilities with process requirements. Capabilities are modeled in two time frames, through which fast (e.g., fatigue) and slow effects (e.g., worsening of illness) become distinguishable. The matchmaking is used in task allocation to establish high-level control over the assistive system. By this approach, inclusive workplaces become autonomously adaptive to the in situ capabilities of the individual person, without the need for customization. Therefore, collaborative workplaces become not only inclusive, but a contributor toward a labor market for all.

Human–robot collaboration (HRC) provides the opportunity to enhance the physical abilities of severely and multiply disabled people thus allowing them to work in industrial workplaces on the primary labour market. In order to assist this target group optimally, the collaborative robot has to support them based on their individual capabilities. Therefore, the knowledge about the amount of required assistance is a central aspect for the design and programming of HRC workplaces. The paper introduces a new method that bases the task allocation on the individual capabilities of a person. The method obtains human capabilities on the one hand and the process requirements on the other. In the following step, these two profiles are compared and the workload of the human is acquired. This determines the amount of support or assistance, which should be provided by a robot capable of HRC. In the end, the profile comparison of an anonymized participant and the concept of the human–robot workplace is presented.

Wire Arc Additive Manufacturing (WAAM) with eccentric wire feed requires defined operating conditions due to the possibility of varying shapes of the deposited and solidified material depending on the welding torch orientation. In consequence, the produced component can contain significant errors because single bead geometrical errors are cumulatively added to the next layer during a building process. In order to minimise such inaccuracies caused by torch manipulation, this article illustrates the concept and testing of object-manipulated WAAM by incorporating robotic and welding technologies. As the first step towards this target, robotic hardware and software interfaces were developed to control the robot. Alongside, a fixture for holding the substrate plate was designed and fabricated. After establishing the robotic setup, in order to complete the whole WAAM process setup, a Gas Metal Arc Welding (GMAW) process was built and integrated into the system. Later, an experimental plan was prepared to perform single and multilayer welding experiments as well as for different trajectories. According to this plan, several welding experiments were performed to decide the parametric working range for the further WAAM experiments. In the end, the results of the first multilayer depositions over intricate trajectories are shown. Further performance and quality optimization strategies are also discussed at the end of this article.