A Standard Interconnect Benchmark for a European In-orbit Services, Manufacturing and Assembly (ISMA) Demonstrator

Wiebke Brinkmann, Mehmed Yüksel, Marko Jankovic, Malte Wirkus, Jona Saffer, Isabel Soto, Jeremi Gancet, Pierre Letier, Thomas A. Schervan, Joerg Kreisel, Stephane Estable, Frank Kirchner

In: In Proc. of. 73rd International Astronautical Congress 2022. International Astronautical Congress (IAC-2022) September 18-22 Paris France n.n. 9/2022.


Growing space debris is an issue for which solutions are being sought, especially with the usage of space robotics. The topic ranges from disposal to sustainability. Modular robotic can be seen is a key factor to support sustainability in space. Within this framework, it is possible to combine modular components in such a way that, for example, a satellite can be created or in the event of malfunction, modules can be replaced without having to abandon the whole satellite. This reduces space debris. To connect the modules, standard interconnects (SIs) with multifunctional features, like to connect mechanically and transmit power and data, are required. In the operational grant (OG) PERIOD of the EU Horizon 2020 project PERASPERA, three existing SIs have been evaluated within a benchmarking concept to give a recommendation on the most suited one to be used in the orbital demonstration mission of PERIOD, as well as provide feedback for their future improvements. Testing was conducted by the German Research Center for Artificial Intelligence GmbH (DFKI) as an independent body to neutrally evaluate the performance of SIs in relevant demonstration scenarios and in full transparency to consortium members. This paper describes the benchmark approach, methodology, test setup, execution, and recommendation path for what concerns the mechanical aspects of SIs. The approach can be extended and applied to future deployments of SIs in European and international space projects.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence