@article{GageikStrohmeierMontenegro2013,
  author    = {Gageik, Nils and Strohmeier, Michael and Montenegro, Sergio},
  title     = {Waypoint flight parameter comparison of an autonomous UAV},
  series = {International Journal of Artificial Intelligence \& Applications (IJAIA)},
  journal   = {International Journal of Artificial Intelligence \& Applications (IJAIA)},
  doi       = {10.5121/ijaia.2013.4304},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96833},
  year      = {2013},
  abstract  = {The present paper compares the effect of different waypoint parameters on the flight performance of a special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus influence the performance of the presented autonomous quadrocopter under real indoor navigation circumstances. Furthermore the paper demonstrates a drawback of the standard potential field method for navigation of such autonomous quadrocopters and points to an improvement.},
  language  = {en}
}
@article{KaiserLeschRotheetal.2020,
  author    = {Kaiser, Dennis and Lesch, Veronika and Rothe, Julian and Strohmeier, Michael and Spieß, Florian and Krupitzer, Christian and Montenegro, Sergio and Kounev, Samuel},
  title     = {Towards Self-Aware Multirotor Formations},
  series = {Computers},
  volume    = {9},
  journal   = {Computers},
  number    = {1},
  issn      = {2073-431X},
  doi       = {10.3390/computers9010007},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-200572},
  pages     = {7},
  year      = {2020},
  abstract  = {In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios.},
  language  = {en}
}
@article{GageikStrohmeierMontenegro2013,
  author    = {Gageik, Nils and Strohmeier, Michael and Montenegro, Sergio},
  title     = {An Autonomous UAV with an Optical Flow Sensor for Positioning and Navigation},
  series = {International Journal of Advanced Robotic Systems},
  journal   = {International Journal of Advanced Robotic Systems},
  doi       = {10.5772/56813},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96368},
  year      = {2013},
  abstract  = {A procedure to control all six DOF (degrees of freedom) of a UAV (unmanned aerial vehicle) without an external reference system and to enable fully autonomous flight is presented here. For 2D positioning the principle of optical flow is used. Together with the output of height estimation, fusing ultrasonic, infrared and inertial and pressure sensor data, the 3D position of the UAV can be computed, controlled and steered. All data processing is done on the UAV. An external computer with a pathway planning interface is for commanding purposes only. The presented system is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application. The focus of this paper is 2D positioning using an optical flow sensor. As a result of the performed evaluation, it can be concluded that for position hold, the standard deviation of the position error is 10cm and after landing the position error is about 30cm.},
  language  = {en}
}