Fuzzy reactive navigation for autonomous mobile robot with an offline adaptive neuro fuzzy system

Zerfa, Houcine; Nouibat, Wahid

doi:10.1109/icosc.2013.6750971

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…The output of ANFIS is the speed 𝑉𝑦 which is the speed of the robot (mm/s) on the 𝑦-coordinate axis in the real world. Where 𝑥 and 𝑦 are inputs at node 𝑖 and 𝐴𝑖, or 𝐵𝑖 − 5, are fuzzy sets corresponding to Gaussian functions as shown in (8).…”

Section: Architecture Of Anfis-based Obstacle Avoidancementioning

confidence: 99%

Obstacle Avoidance Based on Stereo Vision Navigation System for Omni-directional Robot

Umam

Fuad

Suwarno

et al. 2023

Journal of Robotics and Control

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This paper addresses the problem of obstacle avoidance in mobile robot navigation systems. The navigation system is considered very important because the robot must be able to be controlled from its initial position to its destination without experiencing a collision. The robot must be able to avoid obstacles and arrive at its destination. Several previous studies have focused more on predetermined stationary obstacles. This has resulted in research results being difficult to apply in real environmental conditions, whereas in real conditions, obstacles can be stationary or moving caused by changes in the walking environment. The objective of this study is to address the robot’s navigation behaviors to avoid obstacles. In dealing with complex problems as previously described, a control system is designed using Neuro-Fuzzy so that the robot can avoid obstacles when the robot moves toward the destination. This paper uses ANFIS for obstacle avoidance control. The learning model used is offline learning. Mapping the input and output data is used in the initial step. Then the data is trained to produce a very small error. To support the movement of the robot so that it is more flexible and smoother in avoiding obstacles and can identify objects in real-time, a three wheels omnidirectional robot is used equipped with a stereo vision sensor. The contribution is to advance state of the art in obstacle avoidance for robot navigation systems by exploiting ANFIS with target-and-obstacles detection based on stereo vision sensors. This study tested the proposed control method by using 15 experiments with different obstacle setup positions. These scenarios were chosen to test the ability to avoid moving obstacles that may come from the front, the right, or the left of the robot. The robot moved to the left or right of the obstacles depending on the given Vy speed. After several tests with different obstacle positions, the robot managed to avoid the obstacle when the obstacle distance ranged from 173 – 150 cm with an average speed of Vy 274 mm/s. In the process of avoiding obstacles, the robot still calculates the direction in which the robot is facing the target until the target angle is 0.

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Section: Architecture Of Anfis-based Obstacle Avoidancementioning

confidence: 99%

Obstacle Avoidance Based on Stereo Vision Navigation System for Omni-directional Robot

Umam

Fuad

Suwarno

et al. 2023

Journal of Robotics and Control

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“…En [4] se propone un sistema en chip que usa lógica difusa para navegación, este sistema está montado en un FPGA, por lo que aumenta la velocidad de procesamiento del sistema de control. El trabajo en [7], usa un sistema neuro-difuso para la evasión de obstáculos y esta implementado en una computadora la cual se conecta inalámbricamente con un robot que también le comunica las lecturas de sus sensores. Una implementación similar a la propuesta en este trabajo, es la presentada en [2]; en donde los comportamientos de evasión y navegación utilizan un control difuso.…”

Section: Estado Del Arteunclassified

Sistema de navegación y evasión de obstáculos aplicando un sistema de control difuso en una placa Arduino UNO

Cristino¹,

Molina-Lozano²,

Espino³

2019

RCS

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Resumen. La navegación autónoma de robots móviles se ha convertido en unárea de grán interés, debido a su presencia en diversasáreas industriales. En este trabajo se propone la implementación de un sistema de control difuso tipo Mamdani que utiliza la defuzificación del Método del Centro de Máximos (COM), en una plataforma con recursos computacionales limitados (arduino UNO); demostrando así, que es posible implementar controles difusos en sistemas de poco poder computacional sin tener que implementar un sistema de comunicación a una plataforma con mayores recursos (computadora).Palabras clave: conjuntos difusos, lógica difusa, control difuso, robot diferencial, navegación autónoma.Abstract. Autonomous navigation of mobile robots has become an area of great interest, due to its presence in various industrial areas. This paper proposes the implementation of a Mamdani type fuzzy control system that uses the defuzzification of the Maximum Center Method (COM), on a platform with limited computational resources (arduino UNO); thus demonstrating that it is possible to implement fuzzy controls in systems of little computing power without having to implement a communication system to a platform with greater resources (computer).

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A review on the applications of neuro-fuzzy systems in business

Rajab

Sharma

2017

Artif Intell Rev

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Fuzzy reactive navigation for autonomous mobile robot with an offline adaptive neuro fuzzy system

Cited by 4 publications

References 10 publications

Obstacle Avoidance Based on Stereo Vision Navigation System for Omni-directional Robot

Obstacle Avoidance Based on Stereo Vision Navigation System for Omni-directional Robot

Sistema de navegación y evasión de obstáculos aplicando un sistema de control difuso en una placa Arduino UNO

A review on the applications of neuro-fuzzy systems in business

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