A comparison of two camera configurations for optic-flow based navigation of a UAV through urban canyons

We present a comparison of two camera configurations for avoiding obstacles in 3D-space using optic flow. The two configurations were developed for use on an autonomous helicopter, with the aim of enabling it to fly in environments with tall obstacles (e.g. urban canyons). The comparison is made based on real data captured from two sideways-looking cameras and an omnidirectional camera mounted onboard an autonomous helicopter. Optic flow information from the images is used to determine the relative distance to obstacles on each side of the helicopter. We show that on average, both camera configurations are equally effective and that they can be used to tell which of the canyon walls is closer with an accuracy of 74%. It is noted that each configuration is however more effective under certain conditions, and so a suitable hybrid approach is suggested. We also show that there is a linear relationship between the optic flow ratios and the position of the helicopter with respect to the center of the canyon. We use this relationship to develop a proportional control strategy for flying the helicopter along the Voronoi line between buildings.