Abstract
With the continuous expansion of the application field of artificial intelligence-based unmanned vehicles and the rapid development of lidar scanning technology, the application of lidar gradually spread to many artificial intelligence-based unmanned vehicles such as environmental perception, augmented reality, and environmental modeling Technology area. Therefore, the research of lidar in the application of artificial intelligence-based unmanned vehicles has become an inevitable trend in the field of unmanned vehicles. At the same time, the research of lidar data processing technology is of great significance to the development of artificial intelligence unmanned vehicles. This article is based on the research of lidar-based 3D environment modeling technology based on lidar. The research content mainly involves vehicle lidar point cloud 3D environment modeling method, adaptive lidar point cloud data matching algorithm, lidar point cloud-based 3D map modeling application. Through theoretical research and experimental verification of related technical issues, an in-depth study of the three-dimensional terrain modeling technology of unmanned vehicles based on artificial intelligence based on lidar is carried out. This paper proposes a three-dimensional environment modeling method for vehicle lidar point cloud. First, preprocessing processes such as data filtering and terrain segmentation are performed on the original lidar data, and then a three-dimensional geometric model of the environment including surface obstacles and terrain is established through data interpolation and gridding. The verification of the measured data on the typical environment shows the effectiveness of the method.
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Zhang, W., Fu, X., Li, W. (2021). 3D Modeling System of Lidar Point Cloud Processing Algorithm Based on Artificial Intelligence. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_112
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DOI: https://doi.org/10.1007/978-3-030-53980-1_112
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