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Three-dimensional laser point cloud rapid repositioning method

A three-dimensional laser and repositioning technology, applied in image analysis, image enhancement, instruments, etc.

Active Publication Date: 2021-05-07
NANJING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to propose a fast relocation method of 3D laser point cloud to solve the problem of fast relocation of 3D laser point cloud in prior map

Method used

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  • Three-dimensional laser point cloud rapid repositioning method
  • Three-dimensional laser point cloud rapid repositioning method
  • Three-dimensional laser point cloud rapid repositioning method

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Embodiment

[0095] Such as figure 1 As shown, a 3D laser point cloud fast relocation method includes the following steps:

[0096] Step 1. Perform two-dimensional rasterization processing on the original laser image point cloud that has been segmented into the current scene, specifically:

[0097] Step 1-1, the segmented original point cloud of the current frame is removed from the ground point cloud and the snow surface point cloud;

[0098] Step 1-2, such as figure 2 As shown, the centralized processing of the point cloud:

[0099]

[0100] In the formula, the projection grid size is N×N, N=range / res, the lidar observation range is range, the two-dimensional grid resolution is res, and the coordinates of a point in the original point cloud are (p x ,p y ,p z ), the coordinates (x, y, z) after projection;

[0101] Steps 1-3, describe the point cloud in the current frame as p 1 =(x 1 ,y 1 ,z 1 ), p 2 =(x 2 ,y 2 ,z 2 ),...,p n =(x n ,y n ,z n ), determine the centroid...

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Abstract

Disclosed is a three-dimensional laser point cloud rapid relocation method, on the basis of a priori map, the data operand is reduced based on two-dimensional rasterization, the real-time performance is improved, meanwhile, a preliminary candidate scene set is obtained based on a Jaccard coefficient. On this basis, screening is carried out on the preliminary candidate scene set based on a data main direction and a Pearson correlation coefficient to obtain a candidate scene set, so that the real-time performance is improved, three-dimensional clustering is carried out based on an Euclidean clustering method, and then a bipartite graph is constructed for each historical frame scene in the candidate scene set; three-dimensional similarity measurement is completed based on cosine similarity after a maximum matching relation is found based on a Hungarian matching algorithm, and finally a unique candidate scene is obtained, so that the obtained corresponding relation is more reliable in solution, higher in robustness, more accurate in registration result, high in overall real-time performance of the method and high in accuracy. And finally, a 3D-NDT algorithm is utilized to obtain an attitude transformation relation matrix between two frames to complete repositioning. According to the method, unique candidate scene screening is carried out based on cosine similarity.

Description

technical field [0001] The invention belongs to synchronous positioning and mapping technology, in particular to a three-dimensional laser point cloud fast relocation method. Background technique [0002] The relocation algorithm refers to the process of completing the positioning based on the prior map. The relocalization technology directly uses the prior map and the scene information acquired by the current 3D lidar for global positioning, which allows the robot to complete the positioning without reconfiguring the map. [0003] The traditional 3D laser point cloud relocation algorithm is usually based on matching the original point cloud of the 3D scene with key frames in order to obtain candidate scenes, which leads to poor real-time performance of the algorithm, and often needs to reduce the frequency of the relocation algorithm or 3D point cloud input to achieve real-time performance. Require; [0004] At the same time, the traditional relocation algorithm is based ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/30G06K9/62
CPCG06T7/30G06T2207/10028G06F18/23Y02A90/10
Inventor 郭健朱文宇叶雅婷李胜高豪杰
Owner NANJING UNIV OF SCI & TECH
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