淡江大學機構典藏:Item 987654321/126331
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    题名: Implementation of a Small-Sized Mobile Robot with Road Detection, Sign Recognition, and Obstacle Avoidance
    作者: Wong, Ching-Chang;Weng, Kun-Duo;Yu, Bo-Yun;Chou, Yung-Shan
    关键词: : mobile robot;road detection;sign recognition;obstacle avoidance;data augmentation
    日期: 2024.0805
    上传时间: 2024-10-02 12:06:09 (UTC+8)
    摘要: In this study, under the limited volume of 18 cm × 18 cm × 21 cm, a small-sized mobile
    robot is designed and implemented. It consists of a CPU, a GPU, a 2D LiDAR (Light Detection And
    Ranging), and two fisheye cameras to let the robot have good computing processing and graphics
    processing capabilities. In addition, three functions of road detection, sign recognition, and obstacle
    avoidance are implemented on this small-sized robot. For road detection, we divide the captured
    image into four areas and use Intel NUC to perform road detection calculations. The proposed
    method can significantly reduce the system load and also has a high processing speed of 25 frames
    per second (fps). For sign recognition, we use the YOLOv4-tiny model and a data augmentation
    strategy to significantly improve the computing performance of this model. From the experimental
    results, it can be seen that the mean Average Precision (mAP) of the used model has increased by
    52.14%. For obstacle avoidance, a 2D LiDAR-based method with a distance-based filtering mechanism
    is proposed. The distance-based filtering mechanism is proposed to filter important data points and
    assign appropriate weights, which can effectively reduce the computational complexity and improve
    the robot’s response speed to avoid obstacles. Some results and actual experiments illustrate that
    the proposed methods for these three functions can be effectively completed in the implemented
    small-sized robot.
    關聯: Appl. Sci. 2024, 14, 6836.
    DOI: https://doi.org/ 10.3390/app14156836
    显示于类别:[電機工程學系暨研究所] 期刊論文

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