Yazar "Dirik M." seçeneğine göre listele

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    Conclusion and Future Work
    (Springer Science and Business Media Deutschland GmbH, 2021) Dirik M.; Castillo O.; Kocamaz F.
    In this book, we proposed a vision-based kinematic control structure for a wheeled mobile robot (WMR) path planning and path tracking problems in a partially cluttered indoor environment using various heuristics and Soft computing algorithms. The aim was to develop a behavioral strategy for mobile robot navigation in static indoor environments. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Implementation and Evaluation of the Controllers
    (Springer Science and Business Media Deutschland GmbH, 2021) Dirik M.; Castillo O.; Kocamaz F.
    To test the proposed methods in a working environment, we created a LabVIEW simulation environment. This simulation environment was used for testing our proposed methods, and real-time applications realized. This would ensure that the algorithm could be easily developed on a real robot on the purpose of path planning and path tracking. All experiments were performed on a 2.40 GHz dual-core system with 16 GB RAM using a combination of LabVIEW and MATLAB. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Literature Review
    (Springer Science and Business Media Deutschland GmbH, 2021) Dirik M.; Castillo O.; Kocamaz F.
    In this chapter, we have addressed the literature of the various methods used in related work to vision-based control. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Materials and Methods
    (Springer Science and Business Media Deutschland GmbH, 2021) Dirik M.; Castillo O.; Kocamaz F.
    In this book, a mobile robot path planning and path tracking study was carried out. A *, RTT, RRT + Dijkstra, B-RRT, B-RRT + Dijkstra, PRM, APF, GA, Type-1 Fuzzy Logic, and Type-2 Fuzzy Logic algorithms were implemented, and their performances were compared. The utilized performance measurement parameters used here are path length and execution time of the algorithm. The algorithm with the best performance obtained in the scope of these parameters was used in the second stage, which is the path tracking stage. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Preliminary Definitions
    (Springer Science and Business Media Deutschland GmbH, 2021) Dirik M.; Castillo O.; Kocamaz F.
    Path planning, localization, and motion control are common problems in mobile robot control. If the working environment is unstructured and unknown, the navigation problem becomes more difficult. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Robot control with graph based edge measure in real time image frames
    (Institute of Electrical and Electronics Engineers Inc., 2016) Donmez E.; Kocamaz A.F.; Dirik M.
    Robotic path plan extraction is one of the major study area focused with image processing techniques except from estimation based methods, in real time robotic systems. In this study; I. First phase: It is aimed to track a mobile robot and target point by detecting start and target points in real time image frames, continually. II. Second phase: It is aimed to exhibit a novel sensor free kinematic model to determine power ratio transferred to the left and right wheels of the robot with decision tree method by utilizing a graph based method on detected object points. Right and left wheel position, robot center and labeled target positions are acquired with thresholding method by using labels placed on robot. A graph has been created on an image by admitting all detected areas as nodes. The processes of orientating and delivering mobile robot to the target position has been modelled according to distance values of edges between wheels and target. © 2016 IEEE.