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Cites:

Information Journal Paper

Title

CA BASED PATH PLANNING METHOD FOR MOBILE ROBOTS ENHANCED BY ANT COLONY INSPIRED MECHANIS

Pages

  17-26

Abstract

 In PATH PLANNING of MOBILE ROBOTS dealing with concave obstacles is a major challenge. More specifically in real-time planning where there is no complete representation of the environment, this challenge would be much more problematic. In such cases local minimums and high computations cost are the most important problems. In this paper, in order to reduce computational cost, CELLULAR AUTOMATA as a distributed computational method with parallel processing properties is employed as tool for PATH PLANNING purposes. The environment of the robot is modeled as a two dimensional CELLULAR AUTOMATA with four states. Evolutionary rules of the automata are proposed to perform the planning task. The proposed method is appropriate for single robot systems as well as MULTI ROBOT SYSTEMS. The proposed method is afterwards extended to be employed for concave obstacles using an ant colony inspired technique. The most superior advantage of the proposed method is its capability of real-time PATH PLANNING of MOBILE ROBOTS with no need to prior representation of the environment.

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    APA: Copy

    AKBARIMAJD, A., & HASSAN ZADEH, A.. (2011). CA BASED PATH PLANNING METHOD FOR MOBILE ROBOTS ENHANCED BY ANT COLONY INSPIRED MECHANIS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 2(1), 17-26. SID. https://sid.ir/paper/203098/en

    Vancouver: Copy

    AKBARIMAJD A., HASSAN ZADEH A.. CA BASED PATH PLANNING METHOD FOR MOBILE ROBOTS ENHANCED BY ANT COLONY INSPIRED MECHANIS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2011;2(1):17-26. Available from: https://sid.ir/paper/203098/en

    IEEE: Copy

    A. AKBARIMAJD, and A. HASSAN ZADEH, “CA BASED PATH PLANNING METHOD FOR MOBILE ROBOTS ENHANCED BY ANT COLONY INSPIRED MECHANIS,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 2, no. 1, pp. 17–26, 2011, [Online]. Available: https://sid.ir/paper/203098/en

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