Purpose: This research paper aims to create an environment which enables robots to learn from humans by algorithms of Computer Vision and Machine Learning for object detection and gripping. The proposed concept transforms manual picking to highly automated picking performed by robots....

Purpose: A picking system is presented ensuring order fulfilment and enabling transformation from manual to automated picking using a continuous learning process. It is based on Machine Learning for object detection and realized by a human-robot collaboration to meet requirements for flexibility...

Purpose: A primary requirement of Industry 4.0 and realization of Cyber-Physical Systems in production and logistics is the dynamic connection of physical and digital components. Service-oriented Architectures are a well established approach to meet this requirement. However, a service discovery...

Purpose: The automation of picking is still a challenge as a high amount of flexibility is needed to handle different articles according to their requirements. Enabling robot picking in a dynamic warehouse environment consequently requires a sophisticated object detection system capable of...