On contextual perception of workers in complex production environments

In this work we focus on the challenges of perceiving and coordinating spatial actions
between humans and robots in production systems. We address the fundamental questions of how the affective states of individuals in the production process can be visually captured
and interpreted in order to facilitate intuitive interactions without explicit commands.
Additionally, we investigate methods to analyze the environment and action context in a
semantic scene to anticipate user and action intentions. Lastly, we formulate decision
approaches to derive appropriate interaction strategies based on affective user states and
intentions in the scene context to improve productive collaboration between humans and
robots in production environments. By addressing these challenges, this work aims to improve the efficiency of productive teaming processes in production systems.