A method and system for normal scan registration based on combined clustering

A scanning registration and clustering technology, applied in the field of mobile robots, can solve the problems of poor environmental map accuracy and registration result errors, and achieve the effect of accurate classification results

Active Publication Date: 2021-07-30
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a method and system for normal scan registration based on combined clustering. There are errors in the registration results, which leads to the technical problem of poor accuracy of the final environmental map

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  • A method and system for normal scan registration based on combined clustering
  • A method and system for normal scan registration based on combined clustering
  • A method and system for normal scan registration based on combined clustering

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[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0042] like Image 6 As shown, the normal scan registration method based on combined clustering of the present invention comprises the following steps:

[0043] (1) Obtain two continuous lidar points from the mobile robot in real time, the previous lidar point is used as the reference frame (Reference frame), and the latter lidar point is used as the current frame (Current frame);

[0044] lik...

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Abstract

The invention discloses a normal scan registration method based on combined clustering, which includes: obtaining two continuous laser radar point cloud data from a mobile robot in real time, the former laser radar point cloud data as a reference frame, and the latter laser radar point cloud data The point cloud data is used as the current frame, and the reference frame is processed using a density-based spatial clustering algorithm to obtain the initial classification result of the reference frame. For each classification in the initial classification result of the reference frame, determine its two largest singular values Whether the ratio of is greater than the set threshold, if so, use the K-means algorithm to process the classification to obtain K subdivisions, and add these K subdivisions to the final classification set of the reference frame, for the current frame for each lidar point. The invention can solve the technical problem that the existing normal scan registration method adopts grid division, which causes errors in the registration results, and further leads to the poor precision of the finally obtained environment map.

Description

technical field [0001] The invention belongs to the technical field of mobile robots, and more particularly relates to a method and system for normal scan registration based on combined clustering. Background technique [0002] In an unknown environment, simultaneous positioning and map construction are the cornerstones for mobile robots to achieve autonomy, intelligence, and complete more complex tasks. Scanning registration is a prerequisite for the realization of these two functions. [0003] At present, the most common scan registration method is the Normal-distributions transform (NDT) method, which obtains a series of point cloud data in the environment through perceptual sensors (such as lidar and depth cameras). The registration relationship between the two point cloud data is optimized to solve the coordinate transformation relationship between frames, and finally the environment map of the mobile robot's operating area is obtained. [0004] However, for the above-...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S17/89G06K9/62
CPCG01S17/89G06F18/23213G06F18/24
Inventor 陈永府刘田
Owner HUAZHONG UNIV OF SCI & TECH
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