Development of an AGV Controlled by Fuzzy Logic
This paper presents the development of a behavior-based AGV using fuzzy logic. A robot platform and a fuzzy logic controller (FLC) are developed for the embodiment of different behaviors. Experimental results are given to assess the performance of the AGV
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Development of an AGV Controlled by Fuzzy Logic Ramiro S. Barbosa, Manuel F. Silva, and Da´rio J. Oso´rio
Abstract This paper presents the development of a behavior-based AGV using fuzzy logic. A robot platform and a fuzzy logic controller (FLC) are developed for the embodiment of different behaviors. Experimental results are given to assess the performance of the AGV and to validate the proposed design schemes for its construction and control.
29.1
Introduction
Fuzzy logic has emerged in the 1960s, more precisely in 1965, when the first article was published by Zadeh. However, only in the following decade were developed the first applications in the field of automatic control by Mamdani. The control by fuzzy logic allows a different approach to the problem, in which intuitive knowledge on how to best control the process should be acquired, and this information will be part of the FLC. FLCs have been successfully applied in the control of many physical systems, particularly those with uncertainty, unmodelled, disturbed and/or with nonlinear dynamics [1, 2]. Nowadays, one of the main applications of FLC is in the area of autonomous robotics, where several works on behavior-based fuzzy control have been developed [3–5]. Bearing these ideas in mind, this paper presents the development of a mobile robot, with an open and distributed architecture, controlled by fuzzy logic, and capable for the embodiment of different behaviors. The rest of the paper is organized as follows. Section 29.2 addresses the design of the AGV. Section 29.3
R.S. Barbosa (*) • M.F. Silva • D.J. Oso´rio GECAD – Knowledge Engineering and Decision Support Research Center, Institute of Engineering – Polytechnic of Porto (ISEP/IPP), Porto, Portugal e-mail: [email protected]; [email protected]; [email protected] A. Madureira et al. (eds.), Computational Intelligence and Decision Making: Trends and 313 Applications, Intelligent Systems, Control and Automation: Science and Engineering 61, DOI 10.1007/978-94-007-4722-7_29, # Springer Science+Business Media Dordrecht 2013
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is concerned with the design of the fuzzy controller and the implementation of the several behaviors. Section 29.4 presents experimental results showing the effectiveness of the proposed design schemes for the construction and control of the robot. Finally, Sect. 29.5 draws the main conclusions.
29.2
Design of the AGV
29.2.1 AGV Structure The robot is built adopting a modular structure (Fig. 29.1, left), being constituted by a rigid PVC base structure, two DC motors with encoder in the front, four ultrasonic sensors (also called sonars) and a free-wheel in the rear, to support part of the robot weight. The motors can develop a maximum torque of 6.12 kg/cm and a maximum velocity of 66 rpm. The sonars are of the type SRF05, with range from 3 cm to 4 m. Three microcontrollers of the PIC 18F family are used, namely the 18F4585, with a CAN interface for the communication between the several modules of the system. Among other characteristics, the 18F4585 posses
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