Browsing by Author "NADOUR, Mohamed"

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    Intelligent Visual Robot Navigator via Type-2 Fuzzy Logic and Horn-Schunck Methods
    (University of Eloued جامعة الوادي, 2022-01-24) NADOUR, Mohamed; CHERROUN, Lakhmissi; BOUMEHRAZ, Mohamed
    The aim of this paper is to propose a visual navigation control system for a wheeled mobile robot using a type-2 fuzzy logic controller (T2FLC) and Horn-Schunck algorithm (HS) of optical flow (OF) approach. The obstacle avoidance task for an autonomous mobile robot is studied using Takagi-Sugeno fuzzy logic controller based on video acquisition and image processing algorithm. The horn-Schunck algorithm is applied to extract information about the environment and estimate the positions of the surrounding obstacles. The captured image is divided into two parts right and left in order to facilitate the robot motion. Simulation is done using Visual Reality Toolbox in 2D and 3D. The obtained simulation results demonstrate the effectiveness of this autonomous visual navigator.
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    Multi-Robot Visual Navigation Structure based on Lukas-Kanade Algorithm
    (University of Eloued جامعة الوادي, 2022-01-24) ELASRI, Abdelfattah; CHERROUN, Lakhmissi; NADOUR, Mohamed
    This paper presents an efficient control structure of two mobile robots based-visual navigation methods in an indoor environment. The proposed navigators are based on decision systems employed the necessary values estimated by a Lukas-Kanade (LK) algorithm of optical flow (OF) approach. The robots control systems use the generated motion values in order to detect and estimate the positions of the nearest obstacles and objects around each mobile robot. The multi-robot system task is to navigate autonomously in their environment safely without collisions. Obstacles are identified and detected with the employed cameras of each robot based on video acquisition and image processing steps. The efficiency of the proposed approach is verified in simulation using Visual Reality Toolbox. Simulation results demonstrate that the visual based control system allows autonomous navigation without any collision with obstacles..