Papers

20

Total Citations

1,051

H-Index

13

About

Lauro Ojeda is a mobile robotics researcher whose work has profoundly shaped how robots navigate and perceive challenging environments, particularly in off-road and planetary exploration contexts. Based at the University of Michigan's Mobile Robotics Lab, Ojeda has made seminal contributions in three interconnected domains: dead-reckoning and proprioceptive navigation, terrain characterization, and wheel slippage detection. His most influential work includes pioneering methods for precision calibration of fiber-optic gyroscopes to dramatically improve dead-reckoning accuracy (145 citations), and the development of FLEXnav, a fuzzy logic-based position estimation system designed for rugged terrain (85 citations). His research on current-based slippage detection (152 citations) and terrain classification (182 citations) has proven especially impactful for planetary rover applications, directly addressing the dangerous realities of operating robots in unstructured environments. His wheel sinkage and slippage detection work (135 citations) further underscores his focus on making rovers safer and more reliable on surfaces like sand and gravel. With over 900 cumulative citations across his top works, Ojeda's research has become foundational reading for roboticists tackling autonomous navigation in GPS-denied, rough-terrain settings, from Earth-bound field robots to Mars exploration systems.

Research Focus

Key Achievements

13
H-Index
20
Papers
1,051
Total Citations
53
Avg Citations/Paper
🏆 Most Cited Paper
Terrain characterization and classification with a mobile robot
182 citations · 2006
📈 Most Prolific Year: 2006 (4 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Michigan–Ann Arbor, Robotics Research (United States), Michigan United

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago