Create README.md

README.md

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+---
+license: mit
+tags:
+- vision
+- robotics
+- drone-navigation
+- vit
+---
+
+# autonomous_drone_nav_vision
+
+## Overview
+A Vision Transformer (ViT) fine-tuned for tactical aerial navigation. This model enables Small Unmanned Aircraft Systems (sUAS) to classify environmental obstacles and identify safe landing zones in real-time using downward and forward-facing RGB cameras.
+
+
+
+## Model Architecture
+The model utilizes a **Vision Transformer (ViT-Base)** backbone:
+- **Patch Extraction**: Images are divided into $16 \times 16$ fixed-size patches.
+- **Position Embeddings**: Learnable spatial embeddings are added to the patch sequence to retain structural context.
+- **Attention Mechanism**: Global self-attention allows the model to correlate distant visual cues, such as horizon lines and ground markers.
+
+## Intended Use
+- **Obstacle Avoidance**: Integrated into flight control stacks for autonomous "sense and avoid" maneuvers.
+- **Precision Landing**: Identifying designated markers or flat terrain for autonomous recovery.
+- **Search and Rescue**: Preliminary screening of aerial footage to identify human-made structures or anomalies.
+
+## Limitations
+- **Low Light**: Performance degrades significantly in nighttime or heavy fog conditions without thermal input.
+- **Motion Blur**: Rapid yaw movements at high speeds may cause misclassification due to pixel streaking.
+- **Scale Invariance**: Small objects at extreme altitudes may be missed due to the fixed $224 \times 224$ input resolution.