Jari Saarinen

Glaxosmithkline (Finland), Aalto University

Papers

13

Total Citations

133

H-Index

6

About

Jari Saarinen’s research lies at the intersection of field robotics, autonomous navigation, and human-robot teaming, with a focus on enabling robots to operate reliably in unstructured, vegetated environments. His most influential contribution is the development of Normal Distributions Transform (NDT) Traversability Maps, a LIDAR-only approach that allows robots to assess terrain traversability beyond simple geometric obstacles—a critical advance for navigating dense foliage. This work, his top-cited paper (64 citations), addresses a fundamental challenge: distinguishing between impassable obstacles and traversable vegetation. Saarinen further enhanced this capability by integrating ultra-wideband radar data, creating augmented traversability maps that improve obstacle detection in vegetated settings (5–6 citations). His broader portfolio includes sensor-based personal localization systems for incorporating humans into robot teams (16 citations), dynamic modeling for ball-shaped robots (6 citations), and graphical programming frameworks for service robots (6 citations). Through his work on the “Future Worksite” concept and communication frameworks like GIMnet 2.0, Saarinen has advanced the vision of teamwork-centered field robotic systems, making autonomous robots safer and more capable in real-world outdoor applications.

Research Focus

Key Achievements

6
H-Index
13
Papers
133
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Normal Distributions Transform Traversability Maps: LIDAR‐Only Approach for Traversability Mapping in Outdoor Environments
64 citations · 2016
📈 Most Prolific Year: 2004 (2 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Glaxosmithkline (Finland), Aalto University

Top Papers

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    Multientity Rescue System
    4 citations · 2004
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Key Collaborators

Contact & Links

Available for collaboration
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