Papers
11
Total Citations
97
H-Index
6
About
Rachid Latif is a prominent researcher specializing in robotics, embedded systems, and precision agriculture, with particular expertise in Simultaneous Localization and Mapping (SLAM) algorithms and their hardware implementation. His work sits at a compelling intersection of autonomous navigation, computer vision, and intelligent agricultural systems. Latif's most significant contributions center on advancing SLAM algorithms for real-world robotic applications. His foundational work on FastSLAM2.0 acceleration using heterogeneous embedded architectures — including OMAP platforms and high-end GPUs via OpenCL and OpenGL — has helped bridge the gap between computationally demanding localization algorithms and practical deployment constraints. His 2019 survey on SLAM implementation in UAVs (25 citations) has become a key reference for researchers navigating this rapidly evolving field. Beyond robotics, Latif has made meaningful strides in precision agriculture, developing autonomous low-cost robots for greenhouse monitoring and leveraging cutting-edge deep learning models such as YOLOv10 for crop disease detection in strawberry cultivation. His 2022 work on computer-based embedded systems in precision agriculture attracted 16 citations before retraction, reflecting both the relevance and scrutiny his research invites. With over 95 cumulative citations across a decade of publications, Latif represents a versatile and impactful voice in applied robotics and smart agriculture research.
Research Focus
Key Achievements
Top Papers
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- 6SLAM Algorithm: Overview and Evaluation in a Heterogeneous System6 citations · 2021
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