Alex Hatteland
Papers
2
Total Citations
182
H-Index
2
About
Alex Hatteland is a leading researcher in autonomous robotics, specializing in Simultaneous Localization and Mapping (SLAM) for extreme environments. His primary contributions lie in developing robust navigation systems for perceptually-degraded subterranean settings—such as caves, tunnels, and mines—where traditional sensors fail due to poor lighting, uneven terrain, and featureless corridors. Hatteland’s landmark work, "LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments" (2020), has garnered over 180 citations, underscoring its impact on the field. This paper introduced a pioneering framework that integrates multi-modal sensing and resilient algorithms to enable real-time, large-scale mapping and positioning without GPS, overcoming challenges like slippery surfaces and sensor degradation. Hatteland’s research has direct applications in search-and-rescue, mining, and planetary exploration, pushing the boundaries of autonomy in unstructured environments. His achievements include advancing the reliability of SLAM systems in off-nominal conditions, making him a key figure in the evolution of field robotics. For students and researchers, Hatteland’s work exemplifies how theoretical innovation can solve practical, high-stakes problems in the world’s most inaccessible places.
Research Focus
Key Achievements
Top Papers
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