@inproceedings{PonomarjovaWendtFischer-Janzenetal.2024,
  author    = {Ponomarjova, Katrin-Misel and Wendt, Thomas and Fischer-Janzen, Anke and S{\"u}me, Sinan and Kayser, Bastian},
  title     = {Enhancing Independence through Intelligent Robotics: An AI Driven Assistive Robotics Interface},
  booktitle = {UR-AI2023 : The Upper-Rhine Artificial Intelligence Symposium : Artificial Intelligence for Time Series, Robotics and Beyond},
  editor    = {Weber, Jonathan and Lauffenburger, Jean-Philippe},
  organization    = {ENSISA-IRIMAS},
  url       = {https://urai2023.sciencesconf.org/data/pages/book_urai2023_en_2024.pdf},
  institution = {Fakult{\"a}t Wirtschaft (W)},
  pages     = {50 -- 58},
  year      = {2024},
  abstract  = {Applying methods in artificial intelligence to the field of assistive robotics has the potential to increase the independence of people with disabilities. The usage of AI to realize a shared control in this context is controversial, due to the high complexity of everyday tasks and the needed safety requirements. This paper presents the development of a user interface for AI-driven assistive robotic arms (ARA) that aims to assist people with physical disabilities in performing daily activities. This interface allows the user to select object manipulation tasks based on the objects recognized in a live video stream. Further, we compare several state-of-the-art, real-time object detection models to facilitate automatic robotic control. The results demonstrate the feasibility of the model and its potential integration into the overall robotic system.},
  language  = {en}
}