Together with Rhomberg Bau GmbH and convex ZT GmbH, VRVis is developing a concept for the use of Boston Dynamic's robot dog "Spot" for autonomous, immersive construction site documentation.
The research goal of AMASE is to create a suite of tools and methods to ingest, process, visualize, and manipulate heterogeneous, large-scale geospatial data. This data is the constantly updated representation of the real world in the form of an evolving digital twin.
The main goal of this project is to enable a reliable decision support for large-scale infrastructure projects by providing solutions for a collaborative visual analysis of digital twins.
The main objective of the strategic project ARCS is the design of software architectures that enable interactive visualization systems to ingest large volumes and velocities of geospatial and associated non-geometric data.
The applied research project Lightbox 2.0 focuses on the development of a photogrammetric 3D scanner for automatic and deep learning-based modeling of all kinds of keys.
The "Mars-DL" project is investigating how a deep learning system can support the research work of planetary scientists through object and pattern recognition. For this project VRVis has extended the functionality of PRo3D to automatically render shatter cone training images.
MINERVA is an integrated framework for planetary scientists allowing members of different instrument teams to cooperate synergistically in virtual workspaces by sharing observations, analyses and annotations of heterogonous mission data.
Visual Analysis of Asteroid Deflection.
In this project tools and methods for handling, administration, manipulation and evaluation of several different data sources for measurements and lighting design are developed.
Support for planetary research: Visual analysis of reconstructions of the Mars surface and view planning for rover camera instruments.
Virtual exploration and geological analysis of reconstructed Mars surfaces and rock outcrops.
Barrier-free access to art and museums for blind and visually impaired people through 3D technology.
Strategic Research in Scalable, Semantic Rendering.
Planetary Robotics Vision Data Exploitation.
Investigation of techniques enabling a seamless analysis of data from multi-run simulations on multiple degrees of detail.
Algorithms to improve the visual analysis of surface reconstructions.
Decision support systems and 3D viewing technologies for tunnel construction.