aiMotion Lab


Graz | Website

Core facility (CF)

Short Description

The aiMotion Lab allows collaborative and interdisciplinary research in the field of Artificial Intelligence (AI) in connection with mobile and networked electronic objects (such as robots, cars and drones). Experiments in the field of AI research can thus be developed, tested and evaluated in a well-defined environment.

The aiMotion Lab consists of an experiment room at the FH JOANNEUM for the setup and testing of moving cyber-physical systems and a powerful GPU grid at the TU Graz. The experimental room essentially contains an optical tracking system, a measuring station and a control station. The tracking system covers a room of approx. 7 x 7 x 3 meters. Objects in this area can be detected with a position accuracy of up to 0.3 mm and an inclination accuracy of 0.05°. With a frame rate of 360 frames per second, the system is able to track up to 14 fast moving or flying objects. The experimental room was designed in such a way that a Software Defined Radio (SDR) of Graz University of Technology can be easily integrated for measurements. The experiment room is connected to the GPU-Grid of Graz University of Technology via a network infrastructure, so that a real-time interaction between GPU-Grid and experiment room is possible. The objects in the experiment room can communicate with the infrastructure via a wireless connection with latency times of less than 15ms, allowing experiments with decentralized and distributed control algorithms in real time. The GPU-Grid is a cluster consisting of the components network, infrastructure server, storage server and GPU server (3 NVIDIA Tesla V100, 8 NVIDIA Geforce RTX 2080 Ti). The core of the network infrastructure is a fast, modern data center switch for cloud infrastructure that connects the individual servers with each other and with the TU Graz network.

The experiment room of the aiMotion Lab has been set up in such a way that spectators can also follow the experiments. This makes it suitable for both research and teaching tasks.

Contact Person

Andreas Läßer

Research Services

F&D cooperations
Applied, scientific innovation projects
Scientific papers
Faisibility studies
Knowledge transfer

Methods & Expertise for Research Infrastructure

Artificial Intelligence
Internet of Things
Wireless communication
Decentralized Algorithms
real-time control
Indoor tracking system
Indoor positioning system
experimental space

Please contact us:
Andreas Läßer
Graz University of Technology
University of Leoben