Abdelkrim Nemra
Papers
9
Total Citations
95
H-Index
5
About
Abdelkrim Nemra is a robotics researcher whose work sits at the intersection of autonomous navigation, state estimation, and sensor fusion — with a particular focus on Simultaneous Localization and Mapping (SLAM) for unmanned vehicles. His research has made significant contributions to solving the fundamental challenge of enabling robots to navigate and map unknown environments without relying on GPS, a problem of critical importance to the mobile robotics community. Nemra is perhaps best known for pioneering the application of the Smooth Variable Structure Filter (SVSF) to SLAM, developing robust algorithms for both Unmanned Ground Vehicles and Micro Aerial Vehicles. His most-cited work on Indoor SLAM using visual and laser sensor fusion (2015, 23 citations) exemplifies his expertise in combining heterogeneous sensing modalities. He has extended this work to cooperative multi-robot systems, dynamic environments, and multispectral visual odometry — enabling robot localization under challenging day, night, indoor, and outdoor conditions. Across his publication record, Nemra has accumulated over 95 citations, reflecting a steady and growing influence within the autonomous robotics community. His research offers practical algorithmic tools for the next generation of intelligent, self-navigating robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Indoor SLAM for Micro Aerial Vehicles Using Visual and Laser Sensor Fusion23 citations · 2015
- 2
- 3Robust SVSF-SLAM Algorithm for Unmanned Vehicle in Dynamic Environment17 citations · 2018
- 4Multispectral Visual Odometry Using SVSF for Mobile Robot Localization10 citations · 2021
- 5Visual SVSF-SLAM Algorithm Based on Adaptive Boundary Layer Width9 citations · 2018
- 6Real-time Application of SLAM based-line for Unmanned ground vehicle4 citations · 2019
- 7
- 8Cooperative Visual SLAM based on Adaptive Covariance Intersection4 citations · 2018
- 9