Adaptive neuro-fuzzy technique for autonomous ground vehicle navigation

Al-Mayyahi, Auday, Wang, William and Birch, Phil (2014) Adaptive neuro-fuzzy technique for autonomous ground vehicle navigation. Robotics, 3. pp. 349-370. ISSN 2218-6581

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Abstract

This article proposes an adaptive neuro-fuzzy inference system (ANFIS) for
solving navigation problems of an autonomous ground vehicle (AGV). The system consists
of four ANFIS controllers; two of which are used for regulating both the left and right
angular velocities of the AGV in order to reach the target position; and other two ANFIS
controllers are used for optimal heading adjustment in order to avoid obstacles. The two
velocity controllers receive three sensor inputs: front distance (FD); right distance (RD) and
left distance (LD) for the low-level motion control. Two heading controllers deploy the angle
difference (AD) between the heading of AGV and the angle to the target to choose the
optimal direction. The simulation experiments have been carried out under two different
scenarios to investigate the feasibility of the proposed ANFIS technique. The simulation
results have been presented using MATLAB software package; showing that ANFIS is
capable of performing the navigation and path planning task safely and efficiently in a
workspace populated with static obstacles.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Depositing User: Philip Birch
Date Deposited: 19 Nov 2014 14:30
Last Modified: 24 Mar 2017 05:38
URI: http://sro.sussex.ac.uk/id/eprint/51410

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