Fuzzy Control System for Autonomous Navigation of Thymio II Mobile Robots

Boufera, Fatma; Debbat, Fatima; Mondada, Francesco; Khelfi, Mohamed Fayçal

doi:10.4304/jetwi.6.1.101-105

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…We assume that all variables follow a Gaussian probability law; we can describe any each variable by only two values: average x and variance σ 2 of Gaussian. 1 1 ,…”

Section: Estimation Stepmentioning

confidence: 99%

“…Also, Lopes et al [14] describe a proposed navigation system architecture, system mapping, and method of obstacle avoidance for the control of the electric wheelchair " Robchair. " In addition, several control methods used in mobile robotics [1,6,10] are applied in the field of controlling the electric wheelchair. A fuzzy controller was used for determining the robot motion to reach the target, to avoid obstacles, and to navigate.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

Njah

Jallouli

2016

Journal of Intelligent Systems

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The electric wheelchair gives more autonomy and facilitates movement for handicapped persons in the home or in a hospital. Among the problems faced by these persons are collision with obstacles, the doorway, the navigation in a hallway, and reaching the desired place. These problems are due to the difficult manipulation of an electric wheelchair, especially for persons with severe disabilities. Hence, we tried to add more functionality to the standard wheelchair in order to increase movement range, security, environment access, and comfort. In this context, we have developed an automatic control method for indoor navigation. The proposed control system is mounted on the electric wheelchair for the handicapped, developed in the research laboratory CEMLab (Control and Energy Management Laboratory-Tunisia). The proposed method is based on two fuzzy controllers that ensure target achievement and obstacle avoidance. Furthermore, an extended Kalman filter was used to provide precise measurements and more effective data fusion localization. In this paper, we present the simulation and experimental results of the wheelchair navigation system.

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“…We assume that all variables follow a Gaussian probability law; we can describe any each variable by only two values: average x and variance σ 2 of Gaussian. 1 1 ,…”

Section: Estimation Stepmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

Njah

Jallouli

2016

Journal of Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…The complex system, the characteristic of which is usually hard to be described, can be processed by fuzzy control. As a nonlinear intelligent control method with strong robustness and stability, fuzzy control has been used to learn and imitate human behavior and provide the objects which are difficult to be modeled with fuzzy inference and decision and is widely applied in navigation of unmanned aerial vehicles [10], mobile robots [11,12], and so on.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

Gu¹,

Liu²,

Zeng

et al. 2015

Journal of Sensors

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To solve the problem that dynamic Allan variance (DAVAR) with fixed length of window cannot meet the identification accuracy requirement of fiber optic gyro (FOG) signal over all time domains, a dynamic Allan variance analysis method with time-variant window length based on fuzzy control is proposed. According to the characteristic of FOG signal, a fuzzy controller with the inputs of the first and second derivatives of FOG signal is designed to estimate the window length of the DAVAR. Then the Allan variances of the signals during the time-variant window are simulated to obtain the DAVAR of the FOG signal to describe the dynamic characteristic of the time-varying FOG signal. Additionally, a performance evaluation index of the algorithm based on radar chart is proposed. Experiment results show that, compared with different fixed window lengths DAVAR methods, the change of FOG signal with time can be identified effectively and the evaluation index of performance can be enhanced by 30% at least by the DAVAR method with time-variant window length based on fuzzy control.

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Fuzzy Control System for Autonomous Navigation of Thymio II Mobile Robots

Cited by 2 publications

References 12 publications

Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

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