@inproceedings{FingerdeVriesVosetal.2020,
  author    = {Finger, Felix and de Vries, Reynard and Vos, Roelof and Braun, Carsten and Bil, Cees},
  title     = {A comparison of hybrid-electric aircraft sizing methods},
  series = {AIAA Scitech 2020 Forum},
  booktitle = {AIAA Scitech 2020 Forum},
  doi       = {10.2514/6.2020-1006},
  pages     = {31 Seiten},
  year      = {2020},
  language  = {en}
}
@inproceedings{FingerGoettenBraunetal.2019,
  author    = {Finger, Felix and G{\"o}tten, Falk and Braun, Carsten and Bil, Cees},
  title     = {Cost Estimation Methods for Hybrid-Electric General Aviation Aircraft},
  series = {Asia Pacific International Symposium on Aerospace Technology. APISAT 2019},
  booktitle = {Asia Pacific International Symposium on Aerospace Technology. APISAT 2019},
  pages     = {1 -- 13},
  year      = {2019},
  language  = {en}
}
@inproceedings{FingerBraunBil2020,
  author    = {Finger, Felix and Braun, Carsten and Bil, Cees},
  title     = {Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft},
  series = {AIAA SciTech Forum 2020, 06.01.2020 - 10.01.2020, Orlando},
  booktitle = {AIAA SciTech Forum 2020, 06.01.2020 - 10.01.2020, Orlando},
  doi       = {10.2514/6.2020-1502},
  pages     = {15 Seiten},
  year      = {2020},
  language  = {en}
}
@inproceedings{FingerKhalsaKreyeretal.2019,
  author    = {Finger, Felix and Khalsa, R. and Kreyer, J{\"o}rg and Mayntz, Joscha and Braun, Carsten and Dahmann, Peter and Esch, Thomas and Kemper, Hans and Schmitz, O. and Bragard, Michael},
  title     = {An approach to propulsion system modelling for the conceptual design of hybrid-electric general aviation aircraft},
  series = {Deutscher Luft- und Raumfahrtkongress 2019, 30.9.-2.10.2019, Darmstadt},
  booktitle = {Deutscher Luft- und Raumfahrtkongress 2019, 30.9.-2.10.2019, Darmstadt},
  pages     = {15 Seiten},
  year      = {2019},
  abstract  = {In this paper, an approach to propulsion system modelling for hybrid-electric general aviation aircraft is presented. Because the focus is on general aviation aircraft, only combinations of electric motors and reciprocating combustion engines are explored. Gas turbine hybrids will not be considered. The level of the component's models is appropriate for the conceptual design stage. They are simple and adaptable, so that a wide range of designs with morphologically different propulsive system architectures can be quickly compared. Modelling strategies for both mass and efficiency of each part of the propulsion system (engine, motor, battery and propeller) will be presented.},
  language  = {en}
}
@inproceedings{ThomaFisherBertrandetal.2020,
  author    = {Thoma, Andreas and Fisher, Alex and Bertrand, Olivier and Braun, Carsten},
  title     = {Evaluation of possible flight strategies for close object evasion from bumblebee experiments},
  series = {Living Machines 2020: Biomimetic and Biohybrid Systems},
  booktitle = {Living Machines 2020: Biomimetic and Biohybrid Systems},
  editor    = {Vouloutsi, Vasiliki and Mura, Anna and Tauber, Falk and Speck, Thomas and Prescott, Tony J. and Verschure, Paul F. M. J.},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-64312-6},
  doi       = {10.1007/978-3-030-64313-3_34},
  pages     = {354 -- 365},
  year      = {2020},
  language  = {en}
}
@inproceedings{ThomaStiemerBraunetal.2023,
  author    = {Thoma, Andreas and Stiemer, Luc and Braun, Carsten and Fisher, Alex and Gardi, Alessandro G.},
  title     = {Potential of hybrid neural network local path planner for small UAV in urban environments},
  series = {AIAA SCITECH 2023 Forum},
  booktitle = {AIAA SCITECH 2023 Forum},
  publisher = {AIAA},
  doi       = {10.2514/6.2023-2359},
  pages     = {13 Seiten},
  year      = {2023},
  abstract  = {This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17\%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.},
  language  = {en}
}