About

Michel Dufaut is a pioneering researcher in mobile robotics and autonomous navigation, with a career spanning from the 1980s to the 2010s. His core research areas include sensor fusion, motion planning, and vision-based navigation for mobile robots operating in complex, unstructured environments. Dufaut’s major contributions are evident in his development of robust localization methods, such as fusing odometric and magnetometric data (26 citations), and his work on laser-scanner segmentation for robot navigation (79 citations). He also advanced probabilistic road map techniques for motion planning in cluttered settings, applied to virtual reality simulations for nuclear power plant maintenance (80 citations). Notably, Dufaut explored the intersection of robotics and medicine, assessing compressed video quality for tele-surgery applications (22 citations). His research on multisensor reconfiguration and map-building using laser-vision cooperation further underscores his impact on reliable, real-time navigation systems. With over 250 combined citations across his most-cited works, Dufaut’s legacy lies in creating practical, sensor-driven solutions that enhance robot autonomy in challenging environments, making him a key figure in the evolution of mobile robotics.

Research Focus

Key Achievements

8
H-Index
10
Papers
253
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Capture of homotopy classes with probabilistic road map
80 citations · 2003
📈 Most Prolific Year: 1994 (2 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Université de Lorraine, Centre National de la Recherche Scientifique, Centre de Recherche en Automatique de Nancy

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago