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Learning to Optimize UAV Path Planning for Data Sensing in Wireless Sensor Networks

arXiv · AI, language, vision and robotics · article · Sep 15, 2026 · UTC

UAVs have emerged as highly flexible platforms for data sensing in Wireless Sensor Networks (WSNs). Path planning for UAVs in such tasks plays a key role to assure remote sensing effectiveness and friendly energy consumption. However, existing approaches show two key limitations: i) they are primarily hand-crafted with certain design biases that harm adaptation on unseen tasks. ii) they predominantly assume idealized spatial complexities of actual environments through simplified simulation, causing them to underperform during real-world deployment. In this paper, we propose a novel learning-as

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Evidence & attribution

First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.