@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}
}
@article{GoettenFingerHavermannetal.2021,
  author    = {G{\"o}tten, Falk and Finger, Felix and Havermann, Marc and Braun, Carsten and Marino, M. and Bil, C.},
  title     = {Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization},
  series = {CEAS Aeronautical Journal},
  volume    = {12},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-021-00522-w},
  pages     = {589 -- 603},
  year      = {2021},
  abstract  = {The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV's parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft's total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.},
  language  = {en}
}
@inproceedings{SattlerSchneiderAngeleetal.2022,
  author    = {Sattler, Johannes Christoph and Schneider, Iesse Peer and Angele, Florian and Atti, Vikrama and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf},
  title     = {Development of heliostat field calibration methods: Theory and experimental test results},
  series = {SolarPACES conference proceedings},
  booktitle = {SolarPACES conference proceedings},
  number    = {Vol. 1},
  publisher = {TIB Open Publishing},
  address   = {Hannover},
  issn      = {2751-9899 (online)},
  doi       = {10.52825/solarpaces.v1i.678},
  pages     = {9 Seiten},
  year      = {2022},
  abstract  = {In this work, three patent pending calibration methods for heliostat fields of central receiver systems (CRS) developed by the Solar-Institut J{\"u}lich (SIJ) of the FH Aachen University of Applied Sciences are presented. The calibration methods can either operate in a combined mode or in stand-alone mode. The first calibration method, method A, foresees that a camera matrix is placed into the receiver plane where it is subjected to concentrated solar irradiance during a measurement process. The second calibration method, method B, uses an unmanned aerial vehicle (UAV) such as a quadrocopter to automatically fly into the reflected solar irradiance cross-section of one or more heliostats (two variants of method B were tested). The third calibration method, method C, foresees a stereo central camera or multiple stereo cameras installed e.g. on the solar tower whereby the orientations of the heliostats are calculated from the location detection of spherical red markers attached to the heliostats. The most accurate method is method A which has a mean accuracy of 0.17 mrad. The mean accuracy of method B variant 1 is 1.36 mrad and of variant 2 is 1.73 mrad. Method C has a mean accuracy of 15.07 mrad. For method B there is great potential regarding improving the measurement accuracy. For method C the collected data was not sufficient for determining whether or not there is potential for improving the accuracy.},
  language  = {en}
}
@article{ThomessenThomaBraun2023,
  author    = {Thomessen, Karolin and Thoma, Andreas and Braun, Carsten},
  title     = {Bio-inspired altitude changing extension to the 3DVFH* local obstacle avoidance algorithm},
  series = {CEAS Aeronautical Journal},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer},
  address   = {Wien},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-023-00691-w},
  pages     = {11 Seiten},
  year      = {2023},
  abstract  = {Obstacle avoidance is critical for unmanned aerial vehicles (UAVs) operating autonomously. Obstacle avoidance algorithms either rely on global environment data or local sensor data. Local path planners react to unforeseen objects and plan purely on local sensor information. Similarly, animals need to find feasible paths based on local information about their surroundings. Therefore, their behavior is a valuable source of inspiration for path planning. Bumblebees tend to fly vertically over far-away obstacles and horizontally around close ones, implying two zones for different flight strategies depending on the distance to obstacles. This work enhances the local path planner 3DVFH* with this bio-inspired strategy. The algorithm alters the goal-driven function of the 3DVFH* to climb-preferring if obstacles are far away. Prior experiments with bumblebees led to two definitions of flight zone limits depending on the distance to obstacles, leading to two algorithm variants. Both variants reduce the probability of not reaching the goal of a 3DVFH* implementation in Matlab/Simulink. The best variant, 3DVFH*b-b, reduces this probability from 70.7 to 18.6\% in city-like worlds using a strong vertical evasion strategy. Energy consumption is higher, and flight paths are longer compared to the algorithm version with pronounced horizontal evasion tendency. A parameter study analyzes the effect of different weighting factors in the cost function. The best parameter combination shows a failure probability of 6.9\% in city-like worlds and reduces energy consumption by 28\%. Our findings demonstrate the potential of bio-inspired approaches for improving the performance of local path planning algorithms for UAV.},
  language  = {en}
}