Enhancing Digital Twin (DT) technology using Self Learning Autonomous Systems (SLASs)

The DT technology aims to generate a digital (soft) replica of a given object. The benefit of having a DT is important; manufacturers can test their safety-critical objects in a more realistic environment and realize the weaknesses or design errors much before catastrophic incidents occur.

However DT technology naturally requires a strong correlation between the DT and the characteristic properties of the object and is referred as the correlation problem. The correlation problem is challenging and it has to be resolved in order to produce high quality DTs.

A team from the School of Informatics and Space Research Center of the University of Leicester will collaborate with European Space Agency (ESA) and AIRBUS Defence and Space Limited (AIRBUS) consortium to tackle the correlation problem using the SLASs technology. This collaboration will provide enabling technologies for the next generation space technologies and aid the ESA and AIRBUS consortium during their future space shuttle missions.

Team Members: Piyal Samara-Ratna, Dr. Uraz Cengiz Turker, Prof. Ivan Tyukin, Thomas Kappas, and Prof. Richard Ambrosi.

  University of Leicester