Using a USV to efficiently clear uncertainty from aerial images for rescue boat path planning in flooded urban environments
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Abstract
Mapping and path planning in disaster scenarios is an area that has bene ted from aerial imaging and unmanned aerial vehicles (UAVs). However, the integration of an unmanned surface vehicle (USV) in flood rescue operations has not received much attention. We propose a novel map generation and path planning algorithm, which makes use of aerial imaging provided by a UAV in combination with surface level information provided by a USV. Since the aerial image is a 2D projection of a 3D world, some areas of interest could be uncertain, such as under trees. Despite this issue, a Probabilistic Roadmap (PRM) path planning algorithm can be applied to the image in order to nd near-optimal paths for a rescue boat between initial and target locations. With the method proposed here, the preliminary PRM solution is further improved by means of an online feedback structure, where local information provided by the USV is incorporated to the overall map as soon as it becomes available, eliminating uncertainties. Simulation results demonstrate the effectiveness of the proposed approach for improving the time response in search and rescue operations in flooded areas.