@inproceedings{NikolovskiLimpertNessauetal.2023,
  author    = {Nikolovski, Gjorgji and Limpert, Nicolas and Nessau, Hendrik and Reke, Michael and Ferrein, Alexander},
  title     = {Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles},
  series = {2023 IEEE Intelligent Vehicles Symposium (IV)},
  booktitle = {2023 IEEE Intelligent Vehicles Symposium (IV)},
  publisher = {IEEE},
  isbn      = {979-8-3503-4691-6 (Online)},
  doi       = {10.1109/IV55152.2023.10186806},
  pages     = {6 Seiten},
  year      = {2023},
  abstract  = {The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle's drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.},
  language  = {en}
}
@inproceedings{ArndtConzenElsenetal.2023,
  author    = {Arndt, Tobias and Conzen, Max and Elsen, Ingo and Ferrein, Alexander and Galla, Oskar and K{\"o}se, Hakan and Schiffer, Stefan and Tschesche, Matteo},
  title     = {Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers},
  series = {PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments},
  booktitle = {PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments},
  publisher = {ACM},
  isbn      = {9798400700699},
  doi       = {10.1145/3594806.3596558},
  pages     = {535 -- 542},
  year      = {2023},
  abstract  = {This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100\% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.},
  language  = {en}
}