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This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...
This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...
This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...
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