Search

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.

Robotic systems in additive manufacturing (AM) processes offer new possibilities to meet constantly growing requirements for product individualization and small batch sizes. Solids are produced by the layered addition of material, which represents a benefit compared to conventional processes, especially in the production of complex geometries with cavities and undercuts. Recently, research into the entire process of AM from CAD models to the execution of an optimized trajectory has moved into focus. This is motivated by the use of Multidirectional Additive Manufacturing (MDAM) for Wire Arc Additive Manufacturing (WAAM). Since the material is fed eccentrically, the freedom of movement of the welding torch is strongly restricted. The novel procedure of pure manipulation of the component (with six degrees of freedom) can therefore avoid this problem and obtains optimization potentials. This paper gives an overview of the characteristics of MDAM for WAAM processes. Besides an introduction to the extended MDAM process chain, a method for optimizing trajectories is presented and analyzed. To improve the welding result, orientation tolerances are applied to the unique path supporting poses along the welding path. Additionally, implementing a custom cost function for the trajectory optimization has a positive impact on the acceleration and jerk levels. The generated trajectories thus follow the specified welding path with reduced acceleration and jerk.

Robotics : open access journal 10(1), 44 (2021). doi:10.3390/robotics10010044 special issue: "Special Issue "Human–Robot Collaboration" / Special Issue Editors: Prof. Dr. Giacomo Palmieri, Guest Editor; Prof. Dr. Aman Behal, Guest Editor", Published by MDPI, Basel