@article{KrupitzerEberhardingerGerostathopoulosetal.2020,
  author    = {Krupitzer, Christian and Eberhardinger, Benedikt and Gerostathopoulos, Ilias and Raibulet, Claudia},
  title     = {Introduction to the special issue "Applications in Self-Aware Computing Systems and their Evaluation"},
  series = {Computers},
  volume    = {9},
  journal   = {Computers},
  number    = {1},
  issn      = {2073-431X},
  doi       = {10.3390/computers9010022},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203439},
  year      = {2020},
  abstract  = {The joint 1st Workshop on Evaluations and Measurements in Self-Aware Computing Systems (EMSAC 2019) and Workshop on Self-Aware Computing (SeAC) was held as part of the FAS* conference alliance in conjunction with the 16th IEEE International Conference on Autonomic Computing (ICAC) and the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) in Ume{\aa}, Sweden on 20 June 2019. The goal of this one-day workshop was to bring together researchers and practitioners from academic environments and from the industry to share their solutions, ideas, visions, and doubts in self-aware computing systems in general and in the evaluation and measurements of such systems in particular. The workshop aimed to enable discussions, partnerships, and collaborations among the participants. This special issue follows the theme of the workshop. It contains extended versions of workshop presentations as well as additional contributions.},
  language  = {en}
}
@article{GageikBenzMontenegro2015,
  author    = {Gageik, Nils and Benz, Paul and Montenegro, Sergio},
  title     = {Obstacle Detection and Collision Avoidance for a UAV with Complementary Low-Cost Sensors},
  series = {IEEE Access},
  volume    = {3},
  journal   = {IEEE Access},
  doi       = {10.1109/ACCESS.2015.2432455},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125481},
  pages     = {599 - 609},
  year      = {2015},
  abstract  = {This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.},
  language  = {en}
}