A Multi-agent Architecture for Controlling Autonomous Mobile Robots Using Fuzzy Logic and Obstacle Avoidance with Computer Vision

This paper describes the development of a Multi-Agent System (MAS), which is supported with fuzzy logic (to control the robots movements in a reactive path) and computer vision, which controls an autonomous mobile robot to exit a maze. The research consists of two stages. In the first stage the problem is to be able to make the robot exit a maze, the mobile robot is positioned at the entrance (point A) and should reach an output (B), it should be noted that we are working with a NXT robot to Lego MINDSTORMS ®. In its second phase the problem is to make the robot search for a recognized object, for this purpose a camera is used to capture images, which will be processed with vision techniques for identification, and after that, the SMA takes the decision to evade or take the object as appropriate.

[1]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[2]  Christopher L. Scofield,et al.  Neural networks and speech processing , 1991, The Kluwer international series in engineering and computer science.

[3]  P. Melin,et al.  Hybrid neural-based guiding system for mobile robots , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[4]  Chuen-Tsai Sun,et al.  Neuro-fuzzy And Soft Computing: A Computational Approach To Learning And Machine Intelligence [Books in Brief] , 1997, IEEE Transactions on Neural Networks.

[5]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[6]  Chi-Cheng Cheng,et al.  The fuzzy crystallization algorithm: a new approach to complex systems modeling , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[7]  En homenaje,et al.  CONSEJO SUPERIOR DE INVESTIGACIONES CIENTÍFICAS , 2009 .

[8]  Roland Siegwart,et al.  A Control Method for Stable and Smooth Path Following of Mobile Robots , 2005 .

[9]  O. Castillo,et al.  Reactive control of a mobile robot in a distributed environment using fuzzy logic , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[10]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[11]  Constantin V. Negoita,et al.  On Fuzzy Systems , 1978 .

[12]  Farooq Azam,et al.  Biologically Inspired Modular Neural Networks , 2000 .

[13]  Arieh Warshel Neural Networks and Genetic Algorithms , 2002 .