Type-2 fuzzy logic controller optimized by wavelet networks for mobile robot navigation

Affane, Fatma; Omari, Abdelhafid

doi:10.11591/ijeecs.v18.i1.pp326-334

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…The development of smart communication technologies has enabled the emergence of new Location based services (LBSs) applications [16]- [18]. Indeed, indoor localization is a basic process in robotics field [19], [20]. Simultaneous localization and mapping (SLAM) is proposed [21], enabling localization and building maps of an unknown environment.…”

Section: Introductionmentioning

confidence: 99%

An accurate target tracking method in wireless sensor networks

Ahmadi

Bouallègue

2022

IJEECS

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Localization is a challenging research issue in various sectors of activity, particularly in dynamic indoor environment with high perturbation. Many existing localization techniques in wireless sensor networks are not efficient because of many constraints such as the high cost, the memory and energy limitation and the environmental noise effects. Thus, the development of novel methods of localization has become a great concern for the wireless sensor networks. In this paper, we propose a tracking method that combines regression tree and Kalman smoother filtering. Previously, regression tree has been suggested for static positioning by means of received signal strength indicator measurements. In this work, we employ this strategy to solve the mapping relation between these measurements and the target position by means of an optimized propagation model. Moreover, the predicted position considered as the observed information is introduced to the Kalman smoother algorithm, to have more precise state of the moving target. The proposed algorithm has been assessed and compared to other existing methods using real measurements of the received power by the moving target in an indoor environment. The evaluation shows that our solution outperforms other methods regarding localization accuracy.

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Section: Introductionmentioning

confidence: 99%

An accurate target tracking method in wireless sensor networks

Ahmadi

Bouallègue

2022

IJEECS

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“…The latest research trends in robotics have witnessed dramatic advancements in using robots to facilitate human difficult jobs such as the survey of mars or analyses of the sea bottom such applications need that the robot can navigate in unknown environments [1][2][3][4][5][6][7]. The navigation issue is considered one of the most important issues in current research trends in robotics [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Developing a real time navigation for the mobile robots at unknown environments

Abdulredah

Kadhim

2020

IJEECS

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This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the mean square error, especially when increasing the number of landmarks. After that, we simulate and evaluate a mobile robot platform named TurtleBot2e in Gazebo simulator software to achieve the using of the SLAM technique for a different environment using the Rviz library which was built on Robot Operating System in Linux. The main conclusion comes with this work is the simulation and implementation of the SLAM technique using two software platforms separately (MATLAB and ROS) in different unknown environments containing a different number of landmarks so a few number of landmark will make the mobile robot loses its path.

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Type-2 fuzzy logic controller optimized by wavelet networks for mobile robot navigation

Cited by 2 publications

References 11 publications

An accurate target tracking method in wireless sensor networks

An accurate target tracking method in wireless sensor networks

Developing a real time navigation for the mobile robots at unknown environments

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