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.

Thumb degree-of-freedom (DOF) allocation in anthropomorphic robot hands involves a trade-off between functional mobility and mechanical-control complexity. This study presents a controlled multi-metric framework for comparing recurring thumb DOF configurations under common palm geometry, non-thumb finger structure, reference frames, Denavit–Hartenberg kinematics, and sampling assumptions. Five literature-derived thumb configurations, namely 3-1-1, 2-2-1, 2-1-1, 2-0-1, and 1-1-1, were evaluated to determine which thumb DOFs should be preserved when kinematic complexity is reduced. The theoretical evaluation included Kapandji Opposition Test reachability, opposition alignment, workspace volume, workspace compactness, cylindrical grasp opportunity, and Jacobian-based dexterity. A targeted experimental validation of the 2-1-1 and 2-0-1 prototypes was then performed on a tendon-driven test bench. The results showed that qualitatively similar thumb configurations are quantitatively unequal: several designs achieved identical Kapandji scores but differed substantially in workspace, alignment, dexterity, and grasp feasibility. Overall, 3-1-1 achieved the strongest overall capability, while 2-2-1 emerged as the strongest reduced-complexity alternative and achieved the best mean dexterity. Retaining two active carpometacarpal DOFs preserved a large share of dexterous function, whereas metacarpophalangeal fixation maintained selected cylindrical grasps but narrowed the feasible task boundary.