Papers
3
Total Citations
19
H-Index
3
About
Suzanne Lesecq is a leading researcher in embedded systems, sensor fusion, and environment perception, with a particular focus on real-time obstacle detection for autonomous vehicles and wearable assistive technologies. Her work bridges the gap between automotive-grade sensing and portable, low-power applications. She is best known for her contributions to the INSPEX project, where she led the design and integration of a wearable multi-sensor system that brings automotive-equivalent spatial exploration to portable devices, enabling real-time obstacle detection for visually impaired individuals and first responders. Lesecq has also advanced the field of occupancy grid mapping, notably comparing five vehicle detection algorithms for real-time performance in autonomous driving contexts. Her most-cited papers, including the 2019 INSPEX optimization study (7 citations) and the 2017 system integration work (6 citations), demonstrate her impact in creating practical, deployable sensing solutions. Her research is characterized by a strong emphasis on miniaturization, low power consumption, and robust performance under varied environmental conditions, making her a key figure in the evolution of smart spatial exploration systems.
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