ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume II-1/W1
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-1/W1, 33–40, 2015
https://doi.org/10.5194/isprsannals-II-1-W1-33-2015
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-1/W1, 33–40, 2015
https://doi.org/10.5194/isprsannals-II-1-W1-33-2015

  27 Aug 2015

27 Aug 2015

EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES

N. Krombach, D. Droeschel, and S. Behnke N. Krombach et al.
  • Autonomous Intelligent Systems Group, Institute for Computer Science VI, University of Bonn, Bonn, Germany

Keywords: MAVs, Stereo Cameras, Fisheye, Obstacle Detection

Abstract. For autonomous navigation of micro aerial vehicles (MAVs), a robust detection of obstacles with onboard sensors is necessary in order to avoid collisions. Cameras have the potential to perceive the surroundings of MAVs for the reconstruction of their 3D structure. We equipped our MAV with two fisheye stereo camera pairs to achieve an omnidirectional field-of-view. Most stereo algorithms are designed for the standard pinhole camera model, though. Hence, the distortion effects of the fisheye lenses must be properly modeled and model parameters must be identified by suitable calibration procedures. In this work, we evaluate the use of real-time stereo algorithms for depth reconstruction from fisheye cameras together with different methods for calibration. In our experiments, we focus on obstacles occurring in urban environments that are hard to detect due to their low diameter or homogeneous texture.