Author(s)

Bing Cui ¹, Huijun Zhao ¹, Haibo Jiang ¹, Jin Wang ², Jingwen Duan ², Xueping Hu ²

Affiliation(s)

¹ North Mining LTD., Beijing, China
² Racobit Intelligent Traffic System (Beijing) Technology Co., LTD., Beijing, China

Corresponding Author

Bing Cui

ABSTRACT

Mining area is very large, and the road conditions are also very complex. It is very difficult to familiarize oneself with the environment of the mine by driving. Based on 3D LiDAR technology, this research explores a driving boundary detection method for driverless vehicles in mines based on point cloud data. Through the use of 3D LiDAR sensors to obtain point cloud data of the environment, and the use of object shape recognition, high-precision ranging, multi-angle observation and multi-sensor fusion and other technologies, the accurate detection of mine environmental boundaries is realized. The experimental results show that the boundary detection method of mine driverless vehicles based on 3D LiDAR has high accuracy and real-time. Using the point cloud data obtained by the 3D LiDAR sensor, it can quickly capture and represent the shape and contour of objects in the mine environment, and realize accurate boundary detection.

KEYWORDS

Boundary Detection, Autonomous Vehicles, 3D LiDAR, Canny Detection Algorithm

CITE THIS PAPER

Bing Cui, Huijun Zhao, Haibo Jiang, Jin Wang, Jingwen Duan, Xueping Hu, Mining Autonomous Vehicle Driving Boundary Detection on Basis of 3D LiDAR. Journal of Engineering Mechanics and Machinery (2024) Vol. 9: 74-80. DOI: http://dx.doi.org/10.23977/jemm.2024.090112.

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