About

M. Lakrouf is a researcher specializing in autonomous robotics, mobile navigation, and computer vision, with a particular focus on enabling safe and intelligent operation of autonomous systems in complex urban environments. Their work spans several interconnected domains, including object detection, simultaneous localization and mapping (SLAM), and dynamic obstacle perception. Among their most notable contributions is a HOG-based multi-object detection system designed for urban autonomous driving, which has garnered 16 citations and addresses one of the field's most persistent challenges. Complementing this, their research on moving obstacle detection using 2D laser range finders combined with camera systems (15 citations) demonstrates a strong command of sensor fusion for real-time robot perception. Lakrouf has also made significant advances in SLAM efficiency, developing a Fast ICP-SLAM approach tailored for bi-steerable mobile robots operating in large-scale environments — work cited collectively over 20 times across two publications. Their 2016 study on car-like robot navigation in unknown urban areas ties these threads together into a cohesive autonomous transportation framework. Across their body of work, Lakrouf has accumulated over 58 citations, reflecting meaningful influence on the robotics and autonomous systems community and offering valuable methodologies for researchers advancing the frontiers of mobile autonomy.

Research Focus

Key Achievements

5
H-Index
5
Papers
58
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
HOG based multi-object detection for urban navigation
16 citations · 2014
📈 Most Prolific Year: 2015 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Centre de Développement des Technologies Avancées, Université Fédérale de Toulouse Midi-Pyrénées

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago