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About

Harri Kaartinen is a leading researcher at the intersection of laser scanning, robotics, and forestry automation. His work centers on developing precise, real-time 3D mapping and positioning systems to revolutionize forest inventory and machine operations. A key contribution is the pioneering use of under-canopy UAV laser scanning for accurate field measurements (182 citations), demonstrating how robotic platforms can overcome the limitations of traditional aerial surveys in dense forests. Kaartinen has also advanced the integration of mobile laser scanning directly onto forest harvesters, enabling automated tree stem measurement and localization—a critical step toward optimizing the forest value chain. His innovative approach to LiDAR data processing includes exploring raw-stream classification before registration and applying deep neural networks for semantic segmentation of multispectral data, pushing the boundaries of real-time point cloud analysis. Additionally, his work on standalone UWB positioning within forest canopies addresses the fundamental challenge of reliable localization under heavy foliage. Through these contributions, Kaartinen is shaping a future where autonomous machines and advanced sensing transform forest management and environmental monitoring.