Water detection from downwash-induced optical flow for a multirotor UAV

Terrains of different nature exhibit distinct structural dynamics when exposed to wind due to their own intrinsic material composition. This translates into peculiar optical flow patterns that can be used to identify the terrain type. In this sense, this paper proposes an active vision-based water detection model that exploits the predictable optical flow patterns induced by the downwash effect of vertical take-off and landing Unmanned Aerial Vehicles (UAV). To determine whether a water surface is below the UAV, the system tracks the optical flow in the video feed captured by a downward-looking camera. Then, an histogram of optical flow orientation is built and compared against a model histogram, given the expected effect induced by the downwash effect. The histograms are compared and similarity between both histograms is used as the likelihood of the terrain as being covered by water The resulting classification can be used to guide the landing of the UAV or to produce cost maps supporting ground vehicles' safe navigation. The model was successfully validated on 20 videos acquired with an hexacopter while hovering above sandy, grassy, and water-covered terrains.