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AI-based Robust and Failure-Tolerant Processes for In-Orbit Manufacturing of Modular Small Satellites

Mühlbauer, Maximilian Sebastian and Leutert, Florian and Plesker, Christian and Wiedmann, Luis Xaver and Giordano, Alessandro Massimo and Silverio, Joao and Hulin, Thomas and Stulp, Freek and Voges, Jonas and Knobloch, Robert and Schilling, Klaus and Schleich, Benjamin and Albu-Schäffer, Alin Olimpiu (2024) AI-based Robust and Failure-Tolerant Processes for In-Orbit Manufacturing of Modular Small Satellites. In: Proceedings of the International Astronautical Congress, IAC. International Astronautical Congress (IAC), 2024-10-14 - 2024-10-18, Milan, Italy. ISSN 0074-1795.

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Official URL: https://iafastro.directory/iac/paper/id/85912/summary/

Abstract

Advances in small satellite architecture and production processes allow for an increasingly robust automated assembly, enabling the vision of an in-orbit factory. The in-orbit production of satellites promises many advantages: For instance, satellites can be commissioned much faster as they are produced directly at their location of deployment. Also, mechanical requirements are lower as the structure does not need to withstand the vibrations of a rocket launch. This opens new business opportunities with the just-in-time production of large fleets of individualised small satellites which are built according to specific customer needs. As direct human intervention in in-orbit factories is prohibitively expensive, the need for failure tolerant and self-recovering processes arises. The ACOR project leverages AI-based methods for the robust assembly of CubeSats and is built upon three key components: an automated integration and testing process, a failure-tolerant teleoperation interface and a Digital Process Twin (DPT) orchestrating the whole assembly with fault detection, isolation and recovery (FDIR) capabilities. The DPT is the high level decision-making authority of the In-Orbit Factory. It orchestrates the individual participants in the manufacturing process and maps the entire process virtually. Standardised interfaces to the digital twins of product and production machines and the virtual representation of the process are used to find alternative solutions in case of errors. Based on this process information the DPT also performs a long-term optimization of the whole process. The actual assembly of satellites from modular components is performed by a force-sensitive torque-controlled robot. Several FDIR approaches are integrated into individual production steps to supervise the production execution and achieve the required robustness and adaptivity of the process. Automated testing and inspection of individual satellite modules, subsystems up to the whole assembly is seamlessly integrated and performed during the production process to ensure a fully functional satellite at the end of the assembly. A bilateral teleoperation system with force feedback helps to cope with unforseen circumstances. Virtual Fixtures are used to generate guiding forces for the human operator. A probabilistic formulation of these fixtures allows to automatically select the most appropriate fixture and scale the guidance level, balancing human control with automation. This system allows to directly control parts of the assembly, either performing steps that are not automated yet or by completing tasks where the automation has failed. This paper outlines the concept of our robust and failure-tolerant in-orbit factory and presents results achieved with our approach, combining automated and teleoperated assembly with a Digital Process Twin.

Item URL in elib:https://elib.dlr.de/206962/
Document Type:Conference or Workshop Item (Other)
Title:AI-based Robust and Failure-Tolerant Processes for In-Orbit Manufacturing of Modular Small Satellites
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Mühlbauer, Maximilian SebastianUNSPECIFIEDhttps://orcid.org/0000-0002-7635-0248UNSPECIFIED
Leutert, FlorianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Plesker, ChristianTechnical University of Darmstadthttps://orcid.org/0000-0002-5083-7613UNSPECIFIED
Wiedmann, Luis XaverUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Giordano, Alessandro MassimoUNSPECIFIEDhttps://orcid.org/0000-0003-2291-7525UNSPECIFIED
Silverio, JoaoUNSPECIFIEDhttps://orcid.org/0000-0003-1428-8933UNSPECIFIED
Hulin, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-3814-075XUNSPECIFIED
Stulp, FreekUNSPECIFIEDhttps://orcid.org/0000-0001-9555-9517UNSPECIFIED
Voges, JonasTechnical University of DarmstadtUNSPECIFIEDUNSPECIFIED
Knobloch, RobertTechnical University of DarmstadtUNSPECIFIEDUNSPECIFIED
Schilling, KlausUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schleich, BenjaminTechnical University of Darmstadthttps://orcid.org/0000-0002-3638-4179UNSPECIFIED
Albu-Schäffer, Alin OlimpiuUNSPECIFIEDhttps://orcid.org/0000-0001-5343-9074168667745
Date:October 2024
Journal or Publication Title:Proceedings of the International Astronautical Congress, IAC
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
ISSN:0074-1795
Status:Published
Keywords:AI, In-Orbit Factory, Teleoperation, Digital Twin, AIT, Robotic Manufacturing
Event Title:International Astronautical Congress (IAC)
Event Location:Milan, Italy
Event Type:international Conference
Event Start Date:14 October 2024
Event End Date:18 October 2024
Organizer:International Astronautical Federation (IAF)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Telerobotics, R - Explainable Robotic AI
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Mühlbauer, Maximilian Sebastian
Deposited On:01 Oct 2024 12:46
Last Modified:05 Jun 2025 13:03

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