Implementation of a Small-Sized Mobile Robot with Road Detection, Sign Recognition, and Obstacle Avoidance

doi:https://doi.org/ 10.3390/app14156836

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 期刊論文 > Item 987654321/126331

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/126331

Title:	Implementation of a Small-Sized Mobile Robot with Road Detection, Sign Recognition, and Obstacle Avoidance
Authors:	Wong, Ching-Chang;Weng, Kun-Duo;Yu, Bo-Yun;Chou, Yung-Shan
Keywords:	: mobile robot;road detection;sign recognition;obstacle avoidance;data augmentation
Date:	2024.0805
Issue Date:	2024-10-02 12:06:09 (UTC+8)
Abstract:	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.
Relation:	Appl. Sci. 2024, 14, 6836.
DOI:	https://doi.org/ 10.3390/app14156836
Appears in Collections:	[電機工程學系暨研究所] 期刊論文

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