International Journal of Fuzzy Logic Systems (IJFLS)

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International Journal of Fuzzy Logic Systems (IJFLS) https://wireilla.com/ijfls/current.html EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON THE FUZZY LOGIC Hamed Khosravi and Seyed Ghorshi School of Science and Engineering, Sharif University of Technology, International Campus, Kish Island, Iran. ABSTRACT The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model. KEYWORDS Mobile robot, Fuzzy logic, Effective redirecting

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International Journal of Fuzzy Logic Systems
(IJFLS)(IJFLS)
ISSN : 1839 – 6283
http://wireilla.com/ijfls/index.html
Wireilla Scientific Publications

EFFECTIVE REDIRECTING OF THE MOBILE ROBOT
IN A MESSED ENVIRONMENT BASED ON THE
FUZZY LOGIC
Hamed Khosravi and Seyed GhorshiHamed Khosravi and Seyed Ghorshi
AIRCC Publishing CorporationWireilla Scientific Publications

Abstract
The use of fuzzy logic in redirecting mobile robot is based on two sets of received
information. First set is the instantaneous distance of the robot from the obstacle and
second set is the instantaneous information of the robot's position. For this purpose, the
fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance
from obstacles, and the target position relative to the instantaneous orientation of the robot.
In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended
AIRCC Publishing Corporation
In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended
Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the
fuzzy systems are determined based on the estimation of the localization process, the
information of the obstacles center and the target position. Also, the linear acceleration and
instantaneous orientation of the mobile robot are determined by the desired fuzzy
structures which are applied to its kinematic model.
Wireilla Scientific Publications

Keywords
• Mobile robot
• Fuzzy logic
• Effective redirecting
AIRCC Publishing Corporation
• Effective redirecting
Wireilla Scientific Publications

AIRCC Publishing CorporationWireilla Scientific Publications

CONCLUSION
The proposed structure consists of two main subsystems: localization based on the
extended Kalman filter and fuzzy logic based redirecting. In order to form an
automated redirecting system, it is assumed that circular obstacles are located with
determined position in the robot‘s workspace. Also, the target position is specified in
the space. The purpose of the controlling system is to accurately redirect the robot
from source toward target position without collision with obstacles. For this purpose,
AIRCC Publishing Corporation
from source toward target position without collision with obstacles. For this purpose,
two fuzzy systems were considered. The input components of both systems are the
obstacle distance from the center of the left, right, and direct obstacles of the mobile
robot and the target orientation. Based on the information received from these
components and the formation of a suitable fuzzy rule base, the instantaneous
orientation of the robot is determined by the first fuzzy system and the linear
acceleration of the mobile robot by the second fuzzy system.
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