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About

Matthias Linsinger’s research focuses on the intersection of human-robot collaboration, hybrid assembly systems, and the integration of assistance technologies in manufacturing. His work addresses critical challenges in modern production, such as managing increasing product variance and cost pressure through flexible automation. Linsinger’s major contribution is the development of a holistic approach for enabling lightweight robots to adapt to situational task changes in assembly systems, reducing setup times and improving efficiency. His most-cited paper, “Task-based Potential Analysis for Human-Robot Collaboration within Assembly Systems” (2018, 19 citations), provides a framework for evaluating where robots can best augment human workers. In “Situational task change of lightweight robots in hybrid assembly systems” (2019, 9 citations), he further explores how robots can dynamically switch tasks to handle variance. Additionally, his work on a didactic concept for increasing acceptance of consistent data standards (2019, 8 citations) highlights the importance of training and standardization for deploying assistance systems like augmented reality. Linsinger’s research is notable for its practical, industry-oriented approach, offering actionable solutions for smarter, more adaptive factories.