@inproceedings{RekePeterSchulteTiggesetal.2020,
  author    = {Reke, Michael and Peter, Daniel and Schulte-Tigges, Joschua and Schiffer, Stefan and Ferrein, Alexander and Walter, Thomas and Matheis, Dominik},
  title     = {A Self-Driving Car Architecture in ROS2},
  series = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa},
  booktitle = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa},
  publisher = {IEEE},
  address   = {New York, NY},
  isbn      = {978-1-7281-4162-6},
  doi       = {10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020},
  pages     = {1 -- 6},
  year      = {2020},
  abstract  = {In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.},
  language  = {en}
}
@incollection{HarlacherAltepostElsenetal.2024,
  author    = {Harlacher, Markus and Altepost, Andrea and Elsen, Ingo and Ferrein, Alexander and Hansen-Ampah, Adjan and Merx, Wolfgang and Niehues, Sina and Schiffer, Stefan and Shahinfar, Fatemeh Nasim},
  title     = {Approach for the identification of requirements on the design of AI-supported work systems (in problem-based projects)},
  series = {AI in Business and Economics},
  booktitle = {AI in Business and Economics},
  editor    = {Lausberg, Isabel and Vogelsang, Michael},
  publisher = {De Gruyter},
  address   = {Berlin},
  isbn      = {9783110790320},
  doi       = {10.1515/9783110790320},
  pages     = {87 -- 99},
  year      = {2024},
  abstract  = {To successfully develop and introduce concrete artificial intelligence (AI) solutions in operational practice, a comprehensive process model is being tested in the WIRKsam joint project. It is based on a methodical approach that integrates human, technical and organisational aspects and involves employees in the process. The chapter focuses on the procedure for identifying requirements for a work system that is implementing AI in problem-driven projects and for selecting appropriate AI methods. This means that the use case has already been narrowed down at the beginning of the project and must be completely defined in the following. Initially, the existing preliminary work is presented. Based on this, an overview of all procedural steps and methods is given. All methods are presented in detail and good practice approaches are shown. Finally, a reflection of the developed procedure based on the application in nine companies is given.},
  language  = {en}
}
@inproceedings{SchollBartellaMoluluoetal.2019,
  author    = {Scholl, Ingrid and Bartella, Alexander K. and Moluluo, Cem and Ertural, Berat and Laing, Frederic and Suder, Sebastian},
  title     = {MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality},
  series = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen},
  booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  isbn      = {978-3-658-25326-4},
  doi       = {10.1007/978-3-658-25326-4_32},
  pages     = {152 -- 157},
  year      = {2019},
  language  = {en}
}