Autor: Claudio Uriarte

In contrast to the use of robots in standardized production processes, robots must be flexible and adaptable within dynamic logistics processes in order to cope with variable environmental conditions and non-standardized goods. Due to the recent advances in the field of artificial intelligence and networking through industry 4.0, robots will perform complex tasks in logistics in a reliable way in future. A crucial component of a robot system represents the interpretation of the work environment with the help of multi-modal sensor systems, especially image processing systems. This paper describes applications for robotic systems in logistics as well as a concrete example of focusing on the interpretation of multi-modal sensor data for the automation of a logistics task.

The most basic task of conveyor systems in intra-logistics is the transport of goods. For more complex tasks, such as rotating, sorting or layer forming, additional mechanical components are often needed. These range from simple pneumatic cylinders to complex industrial robots. This paper presents the novel and highly flexible conveyor system Celluveyor. Due to the modular design and system architecture, any plant layout can be generated and virtually any material handling task can be realized by a simple software update with one single conveyor system.