Research

For SIListra Systems, research is essential and an integral part of its technology-driven business activities. The focus is on the further development of “coded processing” and “diversified encoded” methods, which implement error diagnosis and handling directly in the software source code of a safety function, thus offering an alternative to conventional hardware safety mechanisms. Our goals are to increase user-friendliness and enable more and more developers to use a software-based, flexible, portable, and more efficient functional security solution.

CoPoRust (2025-11 to 2027-12)

Rust, a modern language with C/C++-like syntax, is becoming increasingly important because it efficiently reports systematic software errors in the development process. This eliminates the need for additional tools and processes that are necessary with C/C++. In combination with code processing, this could prevent both random and systematic errors. The SIListra Safety Transformer does not yet support Rust, which is why the CoPoRust R&D project aims to investigate Rust support. The goal is for the SIListra Safety Transformer to become a tool for detecting random and systematic errors.

Example of a function in Rust.
Example of a function in Rust.

SIListra Systems collaborates again with Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) at the University of Stuttgart for this R&D project.

Funding is provided as part of the Central Innovation Programme for small and medium-sized enterprises (SMEs) (“Zentrales Innovationsprogramm Mittelstand (ZIM)”).

Further information:

BMWE logo and Funded by the BMWE based on a resolution of the German Bundestag

KoSiNuS part 1 (2025-04 to 2025-12) & KoSiNuS part 2 (2026-03 to 2028-03)

Reliable perception is crucial for highly automated or autonomous systems such as agricultural robots.

Together, Hydrive Engineering GmbH, SIListra Systems, Grünspecht Vision Labs GmbH, FusionSystems GmbH, and Fraunhofer IVI will develop key components for perception systems in autonomous machines such as agricultural robots, but also for other applications in industrial automation.

KoSiNuS: Development of central components and safety architectures for use in autonomous mobile machines and systemsCo-financed by the European Union & This measure is co-financed by tax revenue based on the budget approved by the Saxon State Parliament.

Further information:

SafeFloat (2023-01 to 2025-06)

The fields of robotics and sensor evaluation in the area of object recognition require increasingly complex safety systems. In order to master this complexity, the developers of such complex systems want to rely on floating point arithmetic. However, floating-point arithmetic for coded processing has so far only been applicable via “workarounds” such as fixed-point arithmetic or software emulation. In the “SafeFloat” research project, coded processing was extended to support floating point numbers. The R&D project has been carried out in cooperation between SIListra Systems and the Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) at the University of Stuttgart.

SafeFloat: Development of floating point support for coded processing in complex security algorithms

Further information:

Funding was provided as part of the Central Innovation Programme for small and medium-sized enterprises (SMEs) (“Zentrales Innovationsprogramm Mittelstand (ZIM)”).

Logo BMWK and Funded by: Federal Ministry for Economic Affairs and Climate Protection based on a resolution of the German Bundestag

Research allowance (from 2024-01 to 2027-12)

With the research grant from 2024 to 2027, the SIListra Safety Transformer and the underlying platform are being substantially advanced to address current challenges in scalability on multicore systems and in the testability of code generated through Coded Processing.

The SIListra Safety Platform will also integrate AI-based support to automatically generate connections between existing test cases and Coded Processing—using expert systems or language models, for example.

The result is a scalable safety platform for standard hardware that seamlessly combines deterministic multicore execution with efficient testing. This development bridges a critical gap in applying software-based safety systems to safety-critical control applications.

For the first time, Coded Processing will be systematically enabled for scalable and safe parallelization on standard hardware.

Logo FuE BSFZ 2026

Research allowance (from 2020-01 to 2023-12)

The research allowance is also a strategic innovation tool for our company. Our work within the framework of the research allowance has enabled the development of a user-friendly safety concept, on which the SIListra Safety Transformer is still based today. This safety concept is the basis for both the certification of the SIListra Safety Transformer and our broad market entry.

Logo FuE BSFZ 2022