Intuitive robot control via XR glasses
With the help of XR glasses, a robot arm can be seen that is controlled both locally and remotely. The glasses display a digital image of the robot, which users can intuitively control to specify movements. This movement data is transmitted to the actual robot system in real time – precisely, with low latency, and securely. During interaction, additional movement data can be recorded and used to develop neural networks for action recognition. The use of XR glasses and their controllers enables particularly easy operation, allowing even people with no previous experience to safely use the robotic arm. The demonstrator was supported by Intel and shows results from the RICAIP project, which was funded by the EU's Horizon 2020 Research and Innovation Programme.
XR for energy supply, building efficiency, and smart living
The demonstrator shows how augmented reality simplifies access to energy-related information for energy suppliers, housing companies, and end consumers. With the help of augmented reality glasses, the location and condition of power and district heating lines, the energy consumption and energy efficiency of buildings, and the performance data of private heat pumps are displayed as an easy-to-understand layer of information directly over the real environment. This allows technical relationships to be grasped more quickly, decisions to be made more accurately, and the risk of errors to be significantly reduced. The data comes from a Gaia-X-compliant Smart Living Dataspace, which enables the secure, interoperable, and sovereign exchange of sensitive data.
Research results from the 5G Saarlouis project and from ForeSightNEXT, a flagship project funded by the German Federal Ministry of Research, Technology and Space, have been incorporated into the demonstrator.
Dataspace demonstrator for interoperable smart living ecosystems
Dataspaces can be used in practice to enable intelligent networking among different actors. The demonstrator shows an end-to-end process with three data room participants: a housing association that provides energy and building data, an AI service developer that offers a trainable energy forecasting model, and a development company that uses both services. This allows energy data and forecasts to be efficiently processed for a variety of use cases. The dataspace concept provides a basis for making data available in a standardized, interoperable way for AR applications. Semantic annotations, as defined by standards such as ARML 2.0, make AR datasets easier to find and provide developers with a uniform interface for integration into their applications. This demonstrator is also based on results from the ForeSightNEXT project.
Further information
https://unitedxr.eu