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Splicing method and splicing device of Lidar measurement data

A technology for measuring data and cloud data, which is applied in the direction of measuring devices, optical devices, instruments, etc., can solve the problems of heavy matching workload, difficult to deal with continuous noise data, and insufficient accuracy of one-time splicing, and achieve the effect of fast splicing

Inactive Publication Date: 2012-07-25
CHINA UNIV OF MINING & TECH (BEIJING)
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Problems solved by technology

[0006] In the process of realizing the present invention, the inventors found that the splicing method of LiDar scanning data in the above-mentioned prior art has at least the following problems: because the point-by-point calculation method is adopted, the matching workload of feature points between two point cloud data is larger, and for For large-scale point cloud data, the calculation time of the ICP method is too long, and it is difficult to deal with continuous noise data
The accuracy of one splicing is not enough, multiple splicing is needed to improve the splicing quality

Method used

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  • Splicing method and splicing device of Lidar measurement data
  • Splicing method and splicing device of Lidar measurement data

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Embodiment 1

[0024] The processing flow of a splicing method of Lidar measurement data provided by this embodiment is as follows figure 1 As shown, the following processing steps are included:

[0025] Step 11. Organize the paired two point cloud data into a kd (k-dimension, k-dimensional tree) tree, and split the kd tree to generate multiple split units.

[0026] Use LiDAR to collect multiple data of the same object at different positions to obtain multiple point cloud data. The above-mentioned kd tree performs uniform segmentation in eight directions of space to generate multiple segmentation units. Each segmentation unit is a set containing several spatial points p. The data in the segmentation unit is evaluated as a whole, which improves the efficiency of point processing. The Kd tree is an effective tree-like data organization structure. The dimension of each data in the tree is k. The Kd tree divides the data on the one-dimensional with the largest variance in the three-dimensiona...

Embodiment 2

[0084] A splicing device for Lidar measurement data provided by this embodiment, its specific structure is as follows figure 2 As shown, the following modules are included:

[0085] The segmentation unit acquisition module 21 is used to use the laser detection and ranging system LiDAR to perform multiple data acquisitions on the same object at different positions to obtain multiple point cloud data, and perform pairwise pair processing on the multiple point cloud data, and the The paired first point cloud data and second point cloud data are respectively organized with a tree-like data organization structure, and the tree-like data organization structure is evenly segmented in eight directions in space to generate multiple segmentation units; the above-mentioned tree-like data organization structure The data organization structure may be a Kd tree.

[0086] The matching feature unit acquisition module 22 is used to select a set number of segmentation units according to the o...

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Abstract

The embodiment of the invention provides a splicing method and a splicing device of Lidar measurement data. The method mainly comprises the following steps of: carrying out multiple times of data acquisition on the same object in difference positions by utilizing LiDAR so as to acquire multiple point cloud data, carrying out two-to-two paring treatment on the multiple point cloud data, and uniformly segmenting two paired point cloud data to generate multiple segmenting units; selecting multiple feature units from a candidate feature unit set of the two paired point cloud data to form a matched feature unit set; forming a transformation matrix R according to a rotating shaft L and a rotating angle theta, and solving the values of the rotating shaft L and the rotating angle theta according to the principle of minimal error sum of squares of all the matched feature units; transforming all data points in the first point cloud data by virtue of the transformation matrix R and adding the obtained transformation data into the second clod point data to be combined into a complete data set. According to the embodiment of the invention, the feature regions of all the cloud point data and multiple matched feature unit pairs can be accurately and quickly determined based on the working parameters of LiDAE acquisition data, so as to quickly carry out effective splicing on the point cloud data subjected to multiple times of LiDAR sampling.

Description

technical field [0001] The invention belongs to the field of laser detection and measurement, and in particular relates to a method and a device for splicing multiple times of Lidar (Light Detection and Ranging, laser detection and ranging system) measurement data. Background technique [0002] Lidar (Light Detection and Ranging, laser detection and ranging system) uses a single laser pulse to measure the time from the laser source to the measured target, and then from the measured target back to the laser receiver, and combines the orientation data to accurately measure the measured target three-dimensional coordinates. LIDAR has advantages that cannot be replaced by traditional photogrammetry and ground conventional measurement technology, and has the advantages of high degree of automation and high precision. According to different application fields and achievement requirements, combined with flexible loading methods, LiDAR technology can be widely used in basic surveyi...

Claims

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Application Information

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IPC IPC(8): G01B11/24
Inventor 朱红张国英马郁佳
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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