Papers
10
Total Citations
84
H-Index
6
About
Samir Bouaziz is a researcher specializing in embedded systems, autonomous robotics, and real-time implementation of Simultaneous Localization and Mapping (SLAM) algorithms. His work sits at the intersection of robotics, computer vision, and hardware architecture, with a particular focus on reducing the computational complexity of SLAM to make it viable on resource-constrained embedded platforms. Bouaziz's most significant contributions center on accelerating graph-based and particle filter-based SLAM algorithms across heterogeneous, multicore, and low-power architectures, including OMAP processors and FPGAs. His 2016 paper on graph-based SLAM for multicore heterogeneous systems, his most cited work with 14 citations, exemplifies his drive to bridge the gap between algorithmically intensive robotics software and practical embedded deployment. His earlier work on customizing CPU instructions for embedded vision systems (2006, 11 citations) demonstrates a longstanding commitment to hardware-software co-design for autonomous applications. Beyond ground robotics, Bouaziz has extended his research to Unmanned Aerial Vehicles (UAVs), investigating embedded sensor systems and dynamic modeling for fixed-wing platforms. Collectively, his publications reflect a career dedicated to making intelligent autonomous navigation computationally accessible, contributing meaningfully to both the robotics and embedded systems communities.
Research Focus
Key Achievements
Top Papers
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- 5Customizing CPU Instructions for Embedded Vision Systems11 citations · 2006
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- 8Efficient implementation of the graph-based SLAM on an OMAP processor3 citations · 2014
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- 10High-level synthesis for FPGA design based-SLAM application2 citations · 2016