Improving Human-Machine Interaction with a Digital Twin: Adaptive Automation in Container Unloading

Abstract

The unloading of containers is a tedious task that a decreasing number of workers is willing to take on. (Semi-)autonomous systems are already available but limited to clearly defined scenarios due to a rigid level of autonomy. This paper focuses on an adaptive concept for a human-centered semi-autonomous unloading process. First, available systems are analyzed regarding their level of autonomy and the integration of the human operator. Following this, a concept integrating the digital twin and adaptive automation is presented. The usage of a digital representation with adapting autonomy allows combining the strength of humans and machines. In the presented system, the operator uses his cognitive advantage to provide specific support when the machine reaches its limits.