Towards a Framework for Semi-Automated Annotation of Human Order Picking Activities Using Motion Capturing

Data creation for Human Activity Recognition (HAR) requires an immense human effort and contextual knowledge for manual annotation. This paper proposes a framework for semi-automated annotation of sequential data in the order picking process using a motion capturing system. Additionally, it introduces proper annotation labels by defining process steps, human activities and simple human movements in order picking scenarios. An attribute representation based on simple human movements meets the challenges set by the versatility of activities in warehousing.