The project SensAR visualizes sensor data in industrial environments via augmented reality (AR) applications. The research focuses on generalized industrial processes with selected use cases as a basis. Its aim is to support workers using sensor data and digitized assistance systems. The user stories are defined in cooperation with industrial partners.
The goal of the project is to develop sample applications for augmenting the real world with meaningful, context-sensitive information based on retrieved sensor data. The main focus currently lies in supporting three different use cases; facility management, classification and modelling of industrial objects, indoor navigation. The project is a holistic approach that combines research areas such as dynamic object recognition, positioning, sensor technology and standards, UI and data security.
Parts of the project:
Using three example scenarios, possibilities for augmented reality applications will be presented:
Four different use cases were identified and processed, covering a range of technological requirements: objects and sensors from stationary to mobile, required display technology from conventional to AR. The four use cases are RFID measurement chamber, factory layout, load carrier and e-bike. Prototypes were implemented and evaluated for these use cases, which successfully linked the technology components required for the respective use case, from AI-supported object recognition to sensor data exchange and user interface to security requirements. In particular, the RFID measuring chamber and the prototype of an AR-supported operating aid and route navigation to the measuring chamber created for it turned out to be a particularly representative use case. On the one hand, it represents common industrial scenarios such as route guidance to and status display of machines and also requires the linking of a large number of different technology components.
The transfer events, which included demonstrations and discussions in the form of workshops, made it possible to obtain feedback from outside in general and from invited SMEs in particular. This feedback confirmed the prototypical character of the use cases and triggered an exchange of ideas and knowledge. However, the feedback also showed that, as expected, very specific questions arise in industry and especially among SMEs, which require a specifically coordinated implementation in each case. However, this coordination is much easier to implement due to the openly implemented basis and the previous focus on generalisable processes. Within the project, the feasibility of an AR-based visualisation of sensor data in the Industrie 4.0 environment was demonstrated, which outlines the path for future product developments in this area. The goal of providing SMEs with a low-threshold entry into the topic was thus achieved. Further details, such as a film on the path or the final report with the individual results of the work packages, can be found at sensar.hft-stuttgart.de
The following publications/contributions in the form of conference participation, workshops and publications have resulted from the project:
|Management||Prof. Dr Volker Coors, Prof. Dr Eberhard Gülch, Prof. Dr Stefan Knauth, Prof. Dr Gero Lückemeyer, Prof. Dr Franz-Josef Schneider, Prof. Dr Jan Seedorf, Prof. Dr Dieter Uckelmann, Prof. Dr Ursula Voß|
|Partner||Daimler Truck AG, Leuze electronic GmbH + Co KG, Softvise GmbH|
|Funding||Carl Zeiss Foundation|
|Call for proposal||Digitalisierung: Grundlagen erforschen – Anwendungen nutzen|
|Duration||01.04.2019 - 31.03.2022, extended until 30.09.2022|
|Name and position||Field||Email and phone||Room|
|Computer Science and Geodesy||1/121|
|Photogrammetry and Geoinformatics||2/208|
|Faculty for Computer Sciences, Geomatics and Mathematic||2/546|
|Business Information Systems||2/545|
|Internet of Things||2/145|