Text in English ; Abstract: English and Turkish ; Includes bibliographical references (leaves 63-66) ; vi, 69 leaves ; This study is a part of a joint team effort to transform a small-scale model car into an autonomous moving robot. This transformation includes several routines that are essential and attached together. Integration of various equipment on the model car is the first step of that routine which is shared among different thesis studies conducted at RAVLAB (Robotics and Autonomous Vehicles Laboratory) of Işık University. Hence. The resulting hardware system which is explained in this thesis is mostly the co-produce of RAVLAB team. The integration is followed by implementing the software required to establish control and communication links between different units. During this thesis, the author has developed a multi-threaded main control software to facilitate obstacle avoiding movements of the robot while reading and analyzing sensory inputs. This thesis study mainly focuses on detection of the obstacles with visual information collected from an ordinary color camera. The main obstacle detection algorithm that is proposed in this thesis is adapted from a powerful background subtraction algorithm ViBe [1] (Visual Background Extractor). The proposed algorithm uses the model of the ground plane in order to detect obstacles. A different ground plane model is kept for each pixel location as in ViBe. The proposed algorithm is robust against illumination differences, shadows and the changes in the appearance of the ground plane. A comparison is provided (using ground trurh data) with another obstacle detection algorithm [2] which also uses a ground plane based model to detect obstacles. The results of the proposed algorithm under different conditions compared to a counterpart. In addition to the obstacle detection, during this study two obstacle avoidance algorithms are developed to facilitate navigation of the robot in indoor environments. The experiments show that the robot is able to move while avoiding ...


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    Titel :

    Visual obstacle detection and avoidance for indoor mobile robots ; Robot araçlar için kapalı alanda görüntüye dayalı engel tanıma ve engelden sakınma



    Erscheinungsdatum :

    2012-09-19


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629





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