Improved nearest point iteration point cloud registration methods

A technology of closest point iteration and point cloud registration, applied in image data processing, instrumentation, computing, etc., can solve problems such as the total number of iterations, algorithm optimization, etc., to achieve low time cost, improve convergence speed, and optimize the effect of the algorithm

Active Publication Date: 2018-01-30
BEIJING INST OF CONTROL ENG
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AI Technical Summary

Problems solved by technology

[0005] The above-mentioned methods of increasing the search speed of the nearest point and reducing the number of participating point clouds to improve the iteration efficiency of the ICP algorithm all belong to the category of improving the efficiency of a single iteration, and neither optimizes the algorithm from the perspective of reducing the total number of iterations

Method used

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  • Improved nearest point iteration point cloud registration methods
  • Improved nearest point iteration point cloud registration methods

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Embodiment

[0098] The following focuses on comparing the first improved ICP algorithm after adding the construction matrix with the classic ICP algorithm to verify the effectiveness of the improved ICP algorithm. In the comparison process, the same set of model point clouds and point clouds to be registered are used. At the same time, the nearest point search method is the same as the solution method of the rotation and translation matrix, and the Euclidean distance threshold at the end of the iteration is also the same, so that the improvement of adding the construction matrix can be fully compared The difference between the ICP algorithm and the classic ICP algorithm.

[0099] Using classic ICP and improved ICP algorithm will image 3 The point cloud data to be registered and the model data are registered to obtain the attitude of the point cloud to be registered, k 1 and k 2 Take 0.6 and 0.8 respectively. The results compared to Figure 4 and Figure 5 shown.

[0100] Figure 4...

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Abstract

The invention provides two improved nearest point iteration point cloud registration methods, and belongs to the field of image processing and three-dimensional point cloud registration. The method for improving the convergence speed of a nearest point iterative algorithm is based on a traditional nearest point iterative algorithm, and a step of constructing a rotation matrix is added, and the constructed rotating matrix is used for generating new to-be-registered point clouds in an iteration process. Two methods for constructing a matrix are provided. In one way, the matrix is constructed based on the matrix Ri obtained by current iteration, and in the other way, the matrix is constructed according to the difference of the three-axis attitude angle obtained through two adjacent iterations, and through the Eulerian angle formula. Through simulation verification, both methods can effectively improve the convergence speed of a traditional nearest point iterative algorithm, and the overall efficiency of the algorithm is improved. Especially under the condition that the great amount of data points are processed, the advantage of the efficiency improvement is more obvious.

Description

technical field [0001] The invention relates to a point cloud registration method, in particular to an improved closest point iterative point cloud registration method which improves the convergence speed of the closest point iterative algorithm, and belongs to the field of image processing and three-dimensional point cloud registration. Background technique [0002] Acquisition of position and attitude information of non-cooperative target spacecraft in space is a prerequisite for on-orbit approach, control and service. Therefore, the measurement of the position and attitude of non-cooperative targets in space is an important research direction. An effective measurement method is to use the laser-type active measurement sensor to obtain the 3D point cloud of the non-cooperative target in space, and then solve the position and attitude information of the target through the relevant position and attitude calculation algorithm. The solution of position and attitude is general...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/30
Inventor 吴云王立朱飞虎郭绍刚刘达吴奋陟
Owner BEIJING INST OF CONTROL ENG
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