Publications Scientifiques

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Author: search.filters.author.Benatia, Mohamed Akram

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    Advanced Trajectory Planning Technique for Unmanned Underwater Vehicle Navigation with Enhanced Fuzzy Logic Control and Obstacle Avoidance Strategy
    (Springer Science and Business Media, 2025) Demim, Fethi; Saghor, Sofian; Belaidi, Hadjira; Rouigueb, Abdenebi; Messaoui, Ali Zakaria; Benatia, Mohamed Akram; Chergui, Mohamed; Nemra, Abdelkrim; Allam, Ahmed; Kobzili, Elhaouari
    Trajectory planning plays a pivotal role in Unmanned Underwater Vehicles (UUVs), and this study addresses this aspect by employing Rapidly-exploring Random Trees (RRT) and a Fuzzy Logic Control (FLC). The investigation focuses on utilizing the RRT algorithm for waypoint generation in static environments. Leveraging Particle Swarm Optimization (PSO) enhances UUV control by optimizing FLC parameters, ensuring trajectory adherence to obstacle avoidance criteria. Through diverse experimental scenarios, the efficacy of the FLC regulator has been demonstrated, particularly in 3D waypoint navigation using Line-Of-Sight (LOS) guidance, showcasing accurate waypoint navigation, precise course maintenance, and effective pitch and yaw angle control for successful destination arrival. Moreover, this study highlights the increasing importance of RANS simulations in comprehending flow dynamics. It emphasizes a CFD-centric approach for design enhancement and aims to simulate 3D turbulent flow around UUV using ANSYS CFX code. This simulation evaluates appendage effects on overall drag and their interaction with the hull, effectively characterizing hydrodynamic behavior around the defined shape, aligning with study objectives.
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    Smooth Sliding Mode Control Based Technique of an Autonomous Underwater Vehicle Based Localization Using Obstacle Avoidance Strategy
    (Science and Technology Publications, Lda, 2023) Demim, Fethi; Rouigueb, Abdenebi; Belaidi, Hadjira; Messaoui, Ali Zakaria; Bensseghieur, Khadir Lakhdar; Allam, Ahmed; Benatia, Mohamed Akram; Nouri, Abdelmadjid; Nemra, Abdelkrim
    Navigating underwater environments presents serious challenges in control and localization technology. The successful navigation of uncharted territories requires autonomous maneuvers that achieve goals while avoiding obstacles, posing a significant problem to be addressed. Detection-based control using sensor data and obstacle avoidance technology are vital for the autonomy of Autonomous Underwater Vehicles (AUVs). This study focuses on developing a control method based on Sliding Mode Control (SMC) and utilizing an imaging sonar sensor for obstacle avoidance. The proposed approach includes a controller for pitch and depth control, enabling avoidance of stationary objects. A Gaussian potential function is employed to guide the AUV’s maneuvers and avoid obstructions. Numerous simulation results evaluate the control performance of the AUV in realistic simulation conditions, assessing accuracy and stability. The experimental in simulation results demonstrate the excellent performance of our approach in navigating various obstacles such as gentle rise, steep drop-off, and underwater walls, using seafloor environment simulation models.
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    Advanced Trajectory Planning and 3D Waypoints Navigation of Unmanned Underwater Vehicles Based Fuzzy Logic Control with LOS Guidance Technique
    (Science and Technology Publications, Lda, 2023) Demim, Fethi; Belaidi, Hadjira; Rouigueb, Abdenebi; Messaoui, Ali Zakaria; Louadj, Kahina; Saghour, Sofian; Benatia, Mohamed Akram; Chergui, Mohamed; Nemra, Abdelkrim; Allam, Ahmed; Kobzili, Elhaouari
    Trajectory planning is a critical action for achieving the objectives of Unmanned Underwater Vehicles (UUVs). To navigate through complex environments, this study investigates motion trajectory planning using Rapidlyexploring Random Trees (RRT) and Fuzzy Logic Control (FLC). Our goal is to explore the use of the RRT trajectory planning algorithm to generate waypoints in a known static environment. In this case, the UUV’s planned trajectory can meet the required conditions for obstacle avoidance. By using various objective functions, the model can be solved, and the corresponding control variables can be adjusted to effectively accomplish the requirements of underwater navigation. This technique has been successfully applied in various experimental scenarios, demonstrating the effectiveness of the FLC regulator. For instance, The 3D waypoint navigation challenge has been tackled by implementing the Fuzzy Controller, which utilizes the robust Line-Of-Sight (LOS) guidance technique. Experimental results demonstrate that the FLC regulator efficiently navigates through the waypoints, maintains an accurate course, controls the pitch and yaw angles of the UUV, and successfully reaches the final destination.