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cs.RO2026
Field evaluation and optimization of a lightweight autonomous lidar-based UAV system based on a rigorous experimental setup in boreal forest environments
Aleksi Karhunen, Teemu Hakala, Väinö Karjalainen +1
Interest in utilizing autonomous uncrewed aerial vehicles (UAVs) for under-canopy forest remote sensing has increased in recent years, resulting in the publication of numerous auto…
cs.RO2025
Towards autonomous photogrammetric forest inventory using a lightweight under-canopy robotic drone
Väinö Karjalainen, Niko Koivumäki, Teemu Hakala +5
Drones are increasingly used in forestry to capture high-resolution remote sensing data, supporting enhanced monitoring, assessment, and decision-making processes. While operations…
cs.RO2025
Deep Learning-based Robust Autonomous Navigation of Aerial Robots in Dense Forests
Guglielmo Del Col, Väinö Karjalainen, Teemu Hakala +2
Autonomous aerial navigation in dense natural environments remains challenging due to limited visibility, thin and irregular obstacles, GNSS-denied operation, and frequent perceptu…