Nesrine Baklouti

About

Nesrine Baklouti is a researcher specializing in intelligent control systems, autonomous robotics, and fuzzy logic, with a particular focus on advancing navigation and motion planning for mobile robots operating in dynamic, uncertain environments. Her most significant contributions center on the development and application of interval type-2 fuzzy logic systems (IT2FLS), which she has championed as a more robust alternative to traditional type-1 fuzzy logic for handling real-world uncertainties such as measurement noise and imprecise data. Her most cited work, "Interval Type-2 Fuzzy Logic Control of Mobile Robots" (2012, 32 citations), alongside her foundational 2007 paper on motion planning using TSK fuzzy controllers (29 citations), established her as a leading voice in this specialized domain. Baklouti has also explored geometric type-2 fuzzy approaches, hybrid genetic fuzzy modeling for interpretability, and particle swarm optimization (PSO)-based adaptive learning controllers, including applications to the iRobot Create platform. Her integration of computer vision techniques for robot detection and tracking further demonstrates the breadth of her research. Collectively, her work has accumulated over 130 citations, offering meaningful advancements to the robotics and computational intelligence communities.

Research Focus

Key Achievements

Top Papers

1. 1
   Interval Type-2 Fuzzy Logic Control of Mobile Robots

   32 citations · 2012
2. 2
   Motion Planning in Dynamic and Unknown Environment Using an Interval Type-2 TSK Fuzzy Logic Controller

   29 citations · 2007
3. 3
   The geometric interval type-2 fuzzy logic approach in robotic mobile issue

   19 citations · 2009
4. 4
   Accuracy Preserving Interpretability with Hybrid Hierarchical Genetic Fuzzy Modeling: Case of Motion Planning Robot Controller

   14 citations · 2006
5. 5
   Learning system for mobile robot detection and tracking

   13 citations · 2012
6. 6
   Real time PSO based adaptive learning type-2 fuzzy logic controller design for the iRobot Create robot

   9 citations · 2013
7. 7
   Interval type-2 beta fuzzy neural network for wheeled mobile robots obstacles avoidance

   7 citations · 2017
8. 8
   TYPE-2 FUZZY LOGIC CONTROLLER DESIGN USING A REAL-TIME PSO ALGORITHM APPLIED TO “IROBOT CREATE ROBOT

   5 citations · 2017
9. 9
   PSO based adaptive learning Fuzzy Logic Controller for the Irobot Create robot

   5 citations · 2013

Key Collaborators

Contact & Links