Urban terrain three-dimensional reconstruction method based on four-rotor unmanned aerial vehicle laser radar system

Abstract

The invention discloses an urban terrain three-dimensional reconstruction method based on a four-rotor unmanned aerial vehicle laser radar system, which comprises the following steps: 1, acquiring data; 2, integrating data; 3, converting the coordinate system; 4, point cloud denoising; 5, vacuating point cloud; 6, model visualizing. The method can achieve real-time automatic earth surface three-dimensional reconstruction, does not need manual participation, has higher precision and faster speed than traditional image three-dimensional reconstruction methods such as structure recovery from motion and the like, and can be used for various types of low-cost rapid earth surface three-dimensional reconstruction.

Description

technical field [0001] The invention relates to the field of machine vision, specifically a method for three-dimensional reconstruction of urban terrain based on a quadrotor UAV LiDAR system. Background technique [0002] With the development of drone technology, the price of consumer-grade drones continues to drop, and the miniaturization and portability of lidar, it is possible for small and medium-sized drones to carry lidar for geographic surveying and mapping. At present, UAV Lidar surveying and mapping generally uses the method of ground target positioning and ground base station cooperation, but the adaptability to different landforms is not strong, and manual exploration is required in advance to set up targets around the surveying and mapping site. The process is cumbersome and inefficient. The point cloud data obtained at the same time needs to be processed offline at the base station, and the real-time performance is not good enough. [0003] In recent years, wit...

AI Technical Summary

Problems solved by technology

At present, UAV Lidar surveying and mapping generally uses the method of ground target positioning and ground base station cooperation, but the adaptability to different landforms is not strong, and artificial exploration is required in advance to set up targets around the surveying and mapping site. The process is cumbersome and inefficient.

The point cloud data obtained at the same time needs to be processed offline at the base station, and the real-time performance is not good enough

[0003] In recent years, with the development of computer vision and the enhancement of graphics computing capabilities, there have also been technologies that rely on sequential images to recover structures from motion to perform 3D modeling of urban terrain, but the accuracy of modeling by taking pictures is not high enough , prone to model voids and distortions, adjustments after modeling rely on human participation, manual editing and optimization

The model is not accurate enough, and it is easy to mix human subjective factors

The 3D map functions of maps such as Baidu Map also rely on manual modeling, and the proportion of automated modeling is relatively low

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