Papers
20
Total Citations
205
H-Index
10
About
Abdelhafid Elouardi is a researcher whose work sits at the intersection of robotics, embedded systems, and autonomous navigation, with a particular focus on Simultaneous Localization and Mapping (SLAM). Over more than a decade of sustained contributions, he has tackled one of robotics' most computationally demanding challenges: enabling robots to build maps of unknown environments while simultaneously tracking their own position in real time. His early foundational work, including "Design and Evaluation of an Embedded System Based SLAM Applications" (2010), established a trajectory toward efficient hardware implementation that would define his career. A central theme across his most-cited publications is reducing the computational burden of SLAM algorithms — from Extended Kalman Filter and Rao-Blackwellized particle filter approaches to graph-based methods — by leveraging multicore and heterogeneous embedded architectures. His 2021 paper enhancing RGB-D SLAM for indoor localization (26 citations) reflects his continued relevance in the field. More recently, Elouardi has extended his expertise into precision agriculture, applying autonomous robotics and embedded intelligence to greenhouse monitoring and soil mapping. With a portfolio accumulating over 160 citations, his work offers practical, hardware-conscious solutions that bridge theoretical SLAM research and real-world deployment in resource-constrained systems.
Research Focus
Key Achievements
Top Papers
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- 3Efficient implementation of EKF-SLAM on a multi-core embedded system19 citations · 2012
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- 8Design and evaluation of an embedded system based SLAM applications13 citations · 2010
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