Obstacle Avoidance and Cloud Detection for Unmanned Aerial Systems
Daniel P. Schrage, Anthony Joseph Yezzi, Balaji Ganapathy, Sumit Mishra · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2008
Unmanned Aerial Vehicles (UAVs) that operate in civil airspace and ∞y autonomously must have regard for the safety of other vehicles in space the UAV must be equipped with technology for obstacle detection and avoidance. One of the problems with UAVs is the detection and avoidance of clouds and other visual obstructions. In this paper, we propose a system for automated detection of cloud edges as well as the sky regions to maintain operation in visual meteorological conditions using image processing. The solution is based on partial difierential equations (PDE) for image processing. Anisotropic difiusion is a wellknown PDE-based technique and has been widely used in image processing for denoising and segmentation. Recently, new anisotropic difiusion techniques such as anti-geometric difiusion models have been developed which are used for adaptive thresholding and denoising. Using techniques for region merging along with anti-geometric difiusion, helps to separate the scene in a few number of signiflcant regions, thus providing an integrated system for segmentation. This technique works well when there is contrast between the cloud regions and the other areas. To improve the contrast, we propose a preprocessing step of normalizing the input color image where each pixel is treated as a vector. The normalized vector is then projected on the Blue channel. The results obtained by using the modifled scene are shown in the paper. An e‐cient real-time algorithm is being developed so that the algorithm may be used with video sequences. The incorporation of the technique in the UAV simulator tool that is being developed by the co-authors is currently being pursued. I. Introduction Safety is a major concern for Unmanned Aerial Systems (UAS) that operate in civil airspace. The UAS are expected to ∞y autonomously avoiding obstacles and ∞ying through challenging atmospheric conditions. It is desirable that the UAS be equipped with means to maintain operation in visual meteorological conditions while having regard for the safety of other vehicles. One of the major problems with UAS is the detection and avoidance of clouds and other visual obstructions. In this paper, we propose a system for automated detection of cloud edges using image processing. The solution is based on using geometric partial difierential