Fethi Ouerdane
Papers
2
Total Citations
11
H-Index
2
About
Fethi Ouerdane is a leading researcher at the intersection of autonomous robotics, computer vision, and intelligent logistics. His work focuses on deploying multi-domain robotic systems—integrating unmanned aerial vehicles (UAVs) and ground robots—to solve real-world industrial challenges. Ouerdane’s most cited paper, “Technical Aspects of Deploying UAV and Ground Robots for Intelligent Logistics Using YOLO on Embedded Systems” (2025, 7 citations), demonstrates how vision-based AI, particularly YOLO object detection on embedded hardware, can automate logistics to enhance efficiency, reduce costs, and minimize human error while strengthening supply chain resilience. His follow-up work, “Challenges in Multi-domain Robot Swarm for Industrial Mapping and Asset Monitoring” (2025, 4 citations), explores heterogeneous robot swarms that combine ground vehicles and drones for autonomous indoor mapping and asset monitoring in complex industrial environments. By addressing obstacles and enabling self-reinforcement learning, Ouerdane advances the frontier of autonomous exploration. His contributions are pivotal for students and researchers interested in practical, scalable robotics solutions that bridge AI, embedded systems, and industrial automation.
Research Focus
Key Achievements
Top Papers
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