Toward Autonomous UAV Flights in Cluttered Forestry Environments
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Autonomous flight within a forest canopy is a key challenge for generalized scene understanding onboard a future unmanned aerial vehicle (UAV) platform. To address this challenge, see how automatic trail navigation successfully generalizes across differing image resolutions. This allows UAVs with varying sensor payload capabilities to operate equally in such challenging environmental conditions. The optimized deep neural network architecture delivers state-of-the-art performance across varying resolution aerial UAV imagery. Use it to improve forest trail detection for UAV guidance even when using significantly low-resolution images, which are representative of low-cost search and rescue capable UAV platforms.