Transfer of Knowledge and Algorithms from Interdisciplinary Fields of Research to the Measurement of Cargo without Process Interruption

Interdisciplinary research subjects can be used to gain expertise that can be adapted to other applications with similar topics. As a research institute for applied science in the field of factory operation and automation, including material flow technology, we made use of these synergies. Material flow technology deals with the transport of a variety goods. Core tasks are the identification, analysis and tracking of flows, cargo and people. When implementing these objectives using 3D imaging technologies, a variety of challenges has to be addressed. Of particular relevance is the synchronous acquisition and processing of multidimensional sensor data with high frame rates and low exposure times. We have utilized the high demands of image-based motion analysis of athletes from cross-country skiing and rowing, as well as object recognition to enable an autonomous cargo bike and transferred the obtained findings to a logistic freight measurement application. The findings include the tuning of sensors and the enhancement of software performance. This paper discusses the individual projects in more detail, focusing on commonalities in terms of tasks, requirements, technologies and associated problems. Subsequently, the algorithms used are introduced, which are used throughout the several projects to satisfy the demands specified.