Intelligent Navigation in Unstructured Environment by using Memory-Based Reasoning in Embedded Mobile Robot

Nurmaini, Siti (2012) Intelligent Navigation in Unstructured Environment by using Memory-Based Reasoning in Embedded Mobile Robot. European Journal of Scientific Research, 72 (2). pp. 228-244. ISSN 1450-216X

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    This paper deals with the advantages of incorporating memory-based reasoning capabilities in autonomous navigation algorithm. These features enhance the mobile robot’s performance whereby the mobile robot’s forthcoming decisions are also affected by its previous experiences during the navigation apart from the current range inputs. The feasibility of this strategy is applied to an intelligent low cost mobile robot with local sensors with 8 bits microcontroller. The environment of the mobile robot is modeled by classifying temporal sequences of spatial sensory patterns. Fuzzy-Kohonen Network (FKN) technique determines this strategy. A detailed comparison of the proposed technique with other recent approaches in the specific case of ‘local minimum’ detection and obstacle avoidance is also presented. By employing a small number of rules the FKN technique can be adapted for reactive control. This technique provides much faster response to expected events and it allows the mobile robot to continue move without any need to stop for ‘danger’ situation. The effectiveness of the proposed technique is demonstrated also in a series of practical test on our experimental mobile robot in concave and unstructured environment. The results show 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 7 Kbytes resources, and it solve ‘local minima’ situation.

    Item Type: Article
    Subjects: T Technology > T Technology (General)
    Divisions: Faculty of Computer Science > Department of Computer Engineering
    Depositing User: Dr. Ir. MT. Siti Nurmaini Asmawie
    Date Deposited: 09 Apr 2012 15:30
    Last Modified: 09 Apr 2012 15:30

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