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Academic Journal of Engineering and Technology Science, 2024, 7(2); doi: 10.25236/AJETS.2024.070215.

Inspection Robot of Industrial Park Plant Based on Deep Learning


Taimin Gong, Xiaojie Chen, Yuan Shen, Yingying Chen, Fuhao Huang

Corresponding Author:
Taimin Gong

School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China


With the continuous development of modern industrial plants, the demand for traditional manual inspection is increasing. Robotic inspection, as an efficient and accurate alternative, can significantly improve inspection efficiency and reduce labor intensity, while reducing potential safety risks. The goal of this project is to develop a robot based on multi-sensor fusion and SLAM algorithms that can autonomously perform inspection tasks in industrial plants. The robot is equipped with multi-functions such as pedestrian detection, accident detection, and automatic meter reading. At the same time, we will develop an app that connects to the robot's system, through which industrial park staff can remotely control the robot, view water and electricity meter information, and receive alert messages from the robot in a timely manner. This integrated solution will effectively enhance the intelligence level of industrial plants and provide more convenient tools for the management and maintenance of the production environment.


Ros; Yolov5; Src Algorithm; Path Planning

Cite This Paper

Taimin Gong, Xiaojie Chen, Yuan Shen, Yingying Chen, Fuhao Huang. Inspection Robot of Industrial Park Plant Based on Deep Learning. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 2: 96-100. https://doi.org/10.25236/AJETS.2024.070215.


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