human-robot collaboration

Artificial intelligence (AI) can enhance smart assembly by predicting human motion and adapting workplace design. Using probabilistic models such as Gaussian Mixture Models (GMMs), AI systems anticipate operator actions to improve coordination with robots. However, these predictive systems raise ethical concerns related to safety, fairness, and privacy under the EU AI Act, which classifies them as high-risk. This paper presents a conceptual method integrating probabilistic motion modeling with ethical evaluation via Z-Inspection®. An industrial case study using the Smart Work Assistant (SWA) demonstrates how multimodal sensing (motion, gaze) and interpretable models enable anticipatory assistance. The approach moves from ethics evaluation to ethics-informed work design, yielding transferable principles and a configurable assessment matrix that supports compliance-by-design in collaborative assembly.

A newly developed hand guided collaborative robot system will be used for manual mechanical joining process in the final assembly of aircrafts. The tool can be moved quickly and precisely to reach all joining positions avoiding physical effort for the operator. Special focus was given on the integrated handling of the entire system. The interlinked sensory of all subsystems ensures a smart control of the system. A mobile device was implemented to increase the usability and to foster the employees’ acceptance of the solution. It enables significantly improved process documentation, reproducibility and transparency.