SOURCE-LINKED INTELLIGENCE
Learning to Optimize UAV Path Planning for Data Sensing in Wireless Sensor Networks
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
- arXiv · AI, language, vision and robotics · 2026-09-15T04:51:47.000Z
First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.