Chiraz Ben Jabeur
Papers
10
Total Citations
137
H-Index
5
About
Chiraz Ben Jabeur is a robotics and control systems researcher whose work centers on intelligent control strategies for autonomous mobile robots. Specializing in the integration of artificial intelligence techniques — including fuzzy logic, neural networks, and neuro-fuzzy approaches — with classical control frameworks, Ben Jabeur has made significant contributions to the fields of robot navigation, path planning, and obstacle avoidance. Her most impactful work, "Design of a PID Optimized Neural Networks and PD Fuzzy Logic Controllers for a Two-Wheeled Mobile Robot" (2020), has garnered 78 citations and introduced hybrid intelligent controllers that enhance the precision and adaptability of differential mobile robots operating in demanding environments. Across her published research, she has systematically explored diverse control methodologies — from fuzzy logic-based maze navigation to ROS-based SLAM implementation and underwater vehicle depth control — demonstrating a broad and evolving research vision. Her 3D simulation frameworks and recursive neural network predictors further reflect a commitment to practical, deployable robotics solutions. With over 130 cumulative citations, Ben Jabeur's work continues to serve as a valuable reference for researchers and engineers developing next-generation autonomous robotic systems across industrial, agricultural, and military domains.
Research Focus
Key Achievements
Top Papers
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- 3A smart mobile robot commands predictor using recursive neural network11 citations · 2020
- 43D Simulator for Navigation of a Mobile Robot Using Simscape-SIMULINK8 citations · 2019
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- 6Fuzzy Logic Controller for Autonomous Mobile Robot Navigation5 citations · 2019
- 7Implementation of a New-Optimized ROS-Based SLAM for Mobile Robot4 citations · 2022
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