Fethi Demim
Papers
15
Total Citations
200
H-Index
9
About
Fethi Demim is a robotics and autonomous systems researcher whose work centers on simultaneous localization and mapping (SLAM), multi-robot cooperation, and path planning for unmanned ground vehicles (UGVs). He is best known for pioneering the application of the Smooth Variable Structure Filter (SVSF) to SLAM problems, developing robust algorithms that overcome the linearization limitations and modeling inaccuracies that plague traditional approaches such as EKF-SLAM. His most cited work, "Robust SVSF-SLAM for Unmanned Vehicle in Unknown Environment" (2016, 56 citations), established SVSF as a compelling alternative for autonomous navigation in unstructured settings. Demim extended this foundation into cooperative SLAM frameworks, enabling swarms of UGVs to collaboratively build large-scale maps without human intervention, incorporating adaptive covariance intersection techniques to improve decentralized data fusion. His research spans both laser-based and visual SLAM modalities, as well as dynamic environment adaptation. More recently, he has tackled multi-robot path planning using NURBs-based methods for collision avoidance. With over 180 cumulative citations across his published works, Demim has made meaningful contributions to the field of intelligent autonomous vehicles, offering practical solutions that bridge theoretical estimation theory and real-world robotic deployment.
Research Focus
Key Achievements
Top Papers
- 1Robust SVSF-SLAM for Unmanned Vehicle in Unknown Environment56 citations · 2016
- 2Cooperative SLAM for multiple UGVs navigation using SVSF filter25 citations · 2017
- 3
- 4Robust SVSF-SLAM Algorithm for Unmanned Vehicle in Dynamic Environment17 citations · 2018
- 5
- 6
- 7NURBs Based Multi-robots Path Planning with Obstacle Avoidance11 citations · 2024
- 8
- 9Visual SVSF-SLAM Algorithm Based on Adaptive Boundary Layer Width9 citations · 2018
- 10Path planning for Unmanned Ground Vehicle6 citations · 2018