Laurent Trassoudaine
Centre National de la Recherche Scientifique, Université Clermont Auvergne
Papers
4
Total Citations
83
H-Index
3
About
Laurent Trassoudaine is a leading researcher in mobile robotics and 3D perception, with a focus on advancing sensor-based localization, mapping, and object detection. His work is central to enabling robust robotic navigation in challenging environments, particularly through the use of radar and depth sensors. He has made significant contributions to point cloud registration, notably with the development of CICP (Cluster Iterative Closest Point), a method for aligning sparse and dense point clouds that has garnered 38 citations. His research on mobile ground-based radar sensors for simultaneous localization and mapping (SLAM) is highly influential, with 33 citations, demonstrating the value of radar’s long-range and weather-robust capabilities for robotic applications. Trassoudaine has also advanced 3D feature extraction, evaluating keypoint detectors for time-of-flight depth data, and has explored feature aggregation for 3D object detection in industrial settings, contributing to the safety and efficiency of the “Factory of the Future.” His work bridges fundamental perception challenges with practical, real-world robotic systems, making him a key figure in the evolution of autonomous navigation and industrial automation.
Research Focus
Key Achievements
Top Papers
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