Towards Complex Adaptive Control Systems for Human-Robot-Interaction in Intralogistics

Abstract

Due to the rising importance of flexible industrial systems and the involved occurrence of complex robotic systems, the human worker has to be integrated into the system design and its implementation to retain control over changing configurations. This paper introduces a novel way of human-machine-interaction involving humans and autonomous transport vehicles for intralogistics using multi-agent systems. The presented work shows how decentrally organized robots can adapt to human workers sharing the same environment. For that purpose, each entity, also the human worker, is represented by an agent including its specific capabilities and needs. In the resulting multi-agent system, all instances share their information with each other, hence, allowing to adapt dynamically to one another.