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1BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, Germany; 2University of Bremen, Faculty of Production Engineering, Germany
With the increasing popularity of Augmented Reality (AR) applications, especially for mobile devices, the technology supports several construction projects. Here, AR helps to communicate planned construction projects, as its visualization increases the immersion and is better understood than common approaches. However, these use cases are mainly outdoors, which pose special requirements. For most, the (geo-referenced) 3D models of planning projects must be aligned correctly in natural environments, which is a challenge, as many AR devices and standard methods are not working for (large) outdoor environments. For this reason, new research approaches based on different algorithms and sensors arise. This paper defines requirements for developing geo-referenced outdoor AR applications by a structured literature analysis and developing an application with the key requirements: accurate 3D model placement and integration. Creating the mobile outdoor AR application further provides insights for developing such systems. The application considers several outdoor activity requirements and addresses different approaches to geo-referencing with internal and external sensors. This paper also presents two model integration methods: a 2D and a 3D environment scan and algorithmic processing.
Intelligent Pointer Unit to Speed Up the Shelf Replenishment Process in Retail Stores
1Fraunhofer IPA, Germany; 2dm-drogerie markt GmbH & Co. KG
Shelf replenishment is a repetitive, manually executed, and time-consuming task in retail. This paper addresses this issue with an intelligent pointer unit that helps staff reduce the orientation time for small and similar products in the shelf replenishment process. The user wears a ring scanner to scan an article or its box, whereon the pointer unit illuminates the target shelf position received from a digital store model.
A comprehensive evaluation extracts the performance of the pointer unit within two user groups. The results show a reduction of the orientation time of \SI{88.5}{\percent} for beginners, respectively \SI{75}{\percent} for experienced staff members. Furthermore, accounting for the times needed for handling and alignment, a reduction of the overall search time of \SI{71.5}{\percent} for beginners, respectively \SI{22.5}{\percent} for experienced staff members, has been achieved.
