Abdelouahed Tajer
Sup de Co Marrakech, École Normale Supérieure - Marrakech, Cadi Ayyad University
Papers
4
Total Citations
30
H-Index
2
About
Abdelouahed Tajer is a researcher specializing in embedded systems, robotics, and autonomous navigation, with a particular focus on Simultaneous Localization and Mapping (SLAM) algorithms and their efficient implementation on resource-constrained hardware. His work bridges the gap between computationally intensive robotic perception algorithms and the practical constraints of embedded architectures, making real-world autonomous navigation more feasible. Tajer's most significant contributions center on optimizing monocular SLAM systems, particularly the FastSLAM2.0 algorithm, which uses Rao-Blackwellized particle filters to estimate robot poses while simultaneously constructing environmental maps. His 2014 and 2016 papers, each garnering 13 citations, demonstrated how these demanding algorithms could be accelerated on heterogeneous embedded platforms, enabling large-scale deployment with multiple particles. His research into low-power embedded architectures further explored practical trade-offs across multiple SLAM implementations, while his 2021 work extended this investigation to bio-inspired approaches with workload partitioning strategies. Though his citation counts reflect a specialized niche audience, Tajer's contributions address a genuinely challenging problem at the intersection of computer vision, probabilistic robotics, and hardware optimization — work of growing relevance as autonomous systems become increasingly prevalent in everyday applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4