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@MISC{Gorien:1008373,
      author       = {Gorißen, Leon Michel and Schneider, Jan-Niklas and Behery,
                      Mohamed Anwar Abdellatif and Brauner, Philipp and Lennartz,
                      Moritz and Kötter, Ender David and Kaster, Thomas and
                      Kastner, Daniel and Hinke, Christian Rüdiger and Gries,
                      Thomas and Lakemeyer, Gerhard and Ziefle, Martina and
                      Brecher, Christian and Häfner, Constantin Leon},
      title        = {{D}emonstrating {D}ata-to-{K}nowledge {P}ipelines for
                      {C}onnecting {P}roduction {S}ites in the {W}orld {W}ide
                      {L}ab: {D}ata and {S}oftware},
      reportid     = {RWTH-2025-02991},
      year         = {2025},
      abstract     = {This dataset accompanies the publication Demonstrating
                      Data-to-Knowledge Pipelines for Connecting Production Sites
                      in the World Wide Lab. It includes robot trajectory data,
                      trained models, and source code used to develop and validate
                      a foundation model for inverse dynamics control. The dataset
                      captures motion from multiple Franka Emika Panda operating
                      in distinct manufacturing use cases, enabling cross-domain
                      learning and model adaptation. In the project all data is
                      stored in a research data repository with semantic
                      annotations, ensuring findability and interoperability. A
                      release of the raw data is made available here. The
                      foundation model can be fine-tuned for specific
                      applications, supporting efficient robotic control and
                      advancing data-driven manufacturing strategies. As of
                      December 2024 the project is not concluded and future
                      updates might be provided. Links to the datasets and code
                      are provided below with DOIs for accessibility and reuse.
                      <br><br>Funded by the Deutsche Forschungsgemeinschaft (DFG,
                      German Research Foundation) under Germanys Excellence
                      Strategy – EXC-2023 Internet of Production – 390621612.},
      pnm          = {WS-A.III - Functional Perspective (X080067-WS-A.III) / DFG
                      project G:(GEPRIS)390621612 - EXC 2023: Internet of
                      Production (IoP) (390621612)},
      pid          = {G:(DE-82)X080067-WS-A.III / G:(GEPRIS)390621612},
      typ          = {PUB:(DE-HGF)32},
      url          = {https://publications.rwth-aachen.de/record/1008373},
}