Memory-based Reasoning Algorithm Based on Fuzzy-Kohonen Self Organizing Map for Embedded Mobile Robot Navigation

Nurmaini, Siti (2012) Memory-based Reasoning Algorithm Based on Fuzzy-Kohonen Self Organizing Map for Embedded Mobile Robot Navigation. International Journal of Control and Automation, 5 (3). pp. 47-63.

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    Navigation in mobile robot not only avoid obstacles based on the sensor input but also comprehend the nature of its environment, remember over time such comprehended scenarios, recollect them and associate in time perceptions of environment that resemble each other. Such requirements demand spatial and temporal reasoning capabilities, for considering the mobile robot environmental as an experience of a sequence of sensor patterns. Memory-based reasoning must integrate into mobile robot control strategy to produces efficiently movement in unpredictable environment, to achieve robustly and to reduce computational cost. To implement this strategy Fuzzy-Kohonen Network (FKN) technique is utilized by employing small number of rules. The effectiveness of the proposed technique is demonstrated in series of practical test on our experimental mobile robot in structured and unstructured environment. A detailed comparison of the proposed technique with other recent approaches in the specific case of ‘local minima’ detection and obstacle avoidance is also presented. As results found that mobile robot based on FKN technique has the ability to perform navigation tasks in several environments, it has capability to recognize the environment, suitable for low cost mobile robot due to only produce small resources, provides much faster response to expected events and it allows the mobile robot move without any need to stop for ‘danger’ situation without suffering from the ‘local minima’ problem.

    Item Type: Article
    Subjects: T Technology > Computer Engineering
    Divisions: Faculty of Computer Science > Department of Computer Engineering
    Depositing User: Dr. Ir. MT. Siti Nurmaini Asmawie
    Date Deposited: 31 Jan 2014 15:42
    Last Modified: 31 Jan 2014 15:42

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