UAV-Track VLA: Embodied Aerial Tracking via Vision-Language-Action Models

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• UAV-Track VLA achieves a 61.76% success rate in challenging long-distance pedestrian tracking tasks.result 95%
• UAV-Track VLA reduces single-step inference latency by 33.4% compared to the original π₀.₅ model.result 95%
• The proposed method introduces a temporal compression net to efficiently capture inter-frame dynamics.method 90%
• The system demonstrates robust zero-shot generalization in unseen environments.result 85%
• The evaluation benchmark includes a large-scale dataset encompassing over 890K frames, 176 tasks, and 85 diverse objects.method 95%
• The system relies heavily on simulation for evaluation which may not fully replicate real-world conditions.limitation 90%
• The computational demands of processing continuous multimodal inputs could limit real-time effectiveness without significant hardware support.limitation 85%
• UAV-Track VLA achieves 269.65 average tracking frames in long-distance pedestrian tracking tasks.result 95%

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