@article{GageikReinthalBenzetal.2014,
  author    = {Gageik, Nils and Reinthal, Eric and Benz, Paul and Montenegro, Sergio},
  title     = {Complementary Vision based Data Fusion for Robust Positioning and Directed Flight of an Autonomous Quadrocopter},
  doi       = {10.5121/ijaia.2014.5501},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-113621},
  year      = {2014},
  abstract  = {The present paper describes an improved 4 DOF (x/y/z/yaw) vision based positioning solution for fully 6 DOF autonomous UAVs, optimised in terms of computation and development costs as well as robustness and performance. The positioning system combines Fourier transform-based image registration (Fourier Tracking) and differential optical flow computation to overcome the drawbacks of a single approach. The first method is capable of recognizing movement in four degree of freedom under variable lighting conditions, but suffers from low sample rate and high computational costs. Differential optical flow computation, on the other hand, enables a very high sample rate to gain control robustness. This method, however, is limited to translational movement only and performs poor in bad lighting conditions. A reliable positioning system for autonomous flights with free heading is obtained by fusing both techniques. Although the vision system can measure the variable altitude during flight, infrared and ultrasonic sensors are used for robustness. This work is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application and makes autonomous directed flight possible.},
  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}
}