Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration.Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product configuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (eg. tabletop, table legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.

Mobile shopping apps have been using Augmented Reality (AR) in the last years to place their products in the environment of the customer. While this is possible with atomic 3D objects, there is is still a lack in the runtime configuration of 3D object compositions based on user needs and environmental constraints. For this, we previously developed an approach for model-based AR-assisted product configuration based on the concept of Dynamic Software Product Lines. In this demonstration paper, we present the corresponding tool support ProConAR in the form of a Product Modeler and a Product Configurator. While the Product Modeler is an Angular web app that splits products (e.g. table) up into atomic parts (e.g. tabletop, table legs, funnier) and saves it within a configuration model, the Product Configurator is an Android client that uses the configuration model to place different product configurations within the environment of the customer. We show technical details of our ready to use tool-chain ProConAR by describing its implementation and usage as well as pointing out future research directions.