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    Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations

    Access Status
    Fulltext not available
    Authors
    Parasuraman, S.
    Ganapathy, V.
    Shirinzadeh, B.
    Zhong, Yongmin
    Date
    2006
    Type
    Conference Paper
    
    Metadata
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    Citation
    Parasuraman, S. and Ganapathy, V. and Shirinzadeh, Bijian and Zhong, Yongmin. 2006. Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations, in Billingsley, J. (ed), The 13th Annual Conference on Mechatronics and Machine Vision in Practice, Dec 5-7 2006. Toowoomba, QLD: Curran Associates.
    Source Title
    The 13th Annual Conference on Mechatronics and Machine Vision in Practice
    Source Conference
    The 13th Annual Conference on Mechatronics and Machine Vision in Practice
    ISBN
    9781605600871
    URI
    http://hdl.handle.net/20.500.11937/30154
    Collection
    • Curtin Research Publications
    Abstract

    Numerous behavior rule selection mechanisms have been studied and examples of such mechanisms are discussed. Saffiotti (Saffiotti 2000) suggests dividing action selection mechanisms into two groups that he calls arbitration and command fusion which correspond to Mackenzie's (Mackenzie1999) state-based and continuous classes respectively. Behavior arbitration schemes (Pattie Maes 1991) and (Toby Tyrrell 1991) emphasized the testing of hypotheses of behavior rather than solving real-life tasks. Konolige, et al (Kurt Konolige 1992) used fuzzy control in conjunction with modeling and planning techniques to provide reactive guidance of their robot. The shortcomings of the above approaches are as follows: (i) When multiple obstacles present in the environment with equal distances as perceived from multiple sensors of robot, then the corresponding multiple obstacles are treated as a whole and the robot deviates from encountered obstacles widely, avoids obstacles and reaches the target. As a result of the wide deviation, the robot takes longer time and path to reach the target position. (ii)Behavior rule conflicts when multiple obstacles appear in the environment with equal distances from robot.The robot navigation in the optimal path, time and rule selection are more important and becoming critical factors whenever the mobile robots are engaged to search the lives in the event of natural disaster like earthquake etc. The Alpha Level Fuzzy Logic System (ALFLS) is established to resolve the above shortcomings. In this methodology, environmental perceptual field is well defined by a set of control parameters through alpha level intervals of fuzzy sets and their fuzzy membership values respectively. In the proposed method the alpha level threshold maximizes the truth for a particular behavior rule that needs to be fired at a time. The formulation to estimate the defuzzified output of conflicting situation is established theoretically and investigated experimentally and are given in the following sections.

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