Path Planning of An Autonomous Mobile Robot by Integrating Genetic Algorithm and Fuzzy Logic Control

碩士 === 中原大學 === 機械工程研究所 === 91 === The present study concerned about how to guide an autonomous mobile robot (AMR) moving in obstructive environments to avoid obstacles and reach the goal. First, the dynamic equations of the AMR were analyzed. Next, according to the number of obstacles the avoiding...

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Bibliographic Details
Main Authors: Xing-Ren Wang, 王興仁
Other Authors: Cheng-Hsing Hsu
Format: Others
Language:zh-TW
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/88734185318931426571
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Summary:碩士 === 中原大學 === 機械工程研究所 === 91 === The present study concerned about how to guide an autonomous mobile robot (AMR) moving in obstructive environments to avoid obstacles and reach the goal. First, the dynamic equations of the AMR were analyzed. Next, according to the number of obstacles the avoiding behavior were studied, and a path-planning algorithm based on fuzzy control was also proposed. A fuzzy controller was used to modify the moving direction of the AMR. The angle between the obstacle and the goal, and the distance between the obstacle and the AMR were inputs of the controller. A genetic algorithm was used for optimization searching of parameters in design of the controller. The searching parameters included the 5x5 consequent variables of the control rule table, the vertexes of the triangular-shaped membership functions and scaling factors. The fitnessfunction was set as the total traveling length. Optimal controllers were found for various obstructive environments through Matlab simulations.The simulation results showed that the optimal controller obtained for the most complex environment was also fit for the simpler ones.