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Multi-point cloud map fusion method and device based on offline global optimization

A technology of global optimization and map fusion, which is applied to measuring devices, electromagnetic wave re-radiation, radio wave measurement systems, etc., can solve problems such as difficulty in development and high requirements for algorithm implementation, and achieve avoidance of ghosting, flexible and changeable implementation schemes, and algorithms Logical and clear effect

Active Publication Date: 2022-04-12
ZHEJIANG LAB
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Problems solved by technology

However, at present, there are few related studies on multi-point cloud map fusion, and they mainly focus on online methods, which have high requirements for algorithm implementation, are not easy to carry out, and need to balance mapping performance and real-time operation

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  • Multi-point cloud map fusion method and device based on offline global optimization
  • Multi-point cloud map fusion method and device based on offline global optimization
  • Multi-point cloud map fusion method and device based on offline global optimization

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Embodiment Construction

[0035] In order to make the object, technical solution and technical effect of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0036] Such as figure 1 Shown, a kind of multi-point cloud map fusion method based on off-line global optimization of the present invention, comprises the following steps:

[0037] Step 1. Adapt the laser SLAM method based on GPS information initialization, and build self-constraint through the laser SLAM method: based on the open source laser SLAM method—LIO-SAM process, perform GPS information initialization adaptation, and use open source laser SLAM at the same time Key frame pose information, point cloud information and constraint information are retained during and at the end of the method, where the constraint information includes: odometer factor, GPS factor and loop closure factor.

[0038] Specifically, the following sub-steps are i...

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Abstract

The invention discloses a multi-point cloud map fusion method and device based on off-line global optimization. The method comprises the following steps: step 1, adapting to a laser SLAM method based on GPS information initialization; 2, a plurality of point cloud maps are sequentially obtained from a plurality of data sets needing to be used for point cloud fusion according to the online laser SLAM method in the S1; step 3, loading information of each point cloud map offline, and sequentially constructing an odometer factor, a loopback factor and a GPS (Global Positioning System) factor of each point cloud map; 4, constructing mutual constraint factors between different point cloud maps; and 5, setting optimization parameters, carrying out global optimization, and storing the final fusion point cloud and all key frame information. Compared with an online multi-point cloud map fusion method, the multi-point cloud map fusion method has the advantages that the stability and reliability of multi-point cloud map fusion are improved, the algorithm implementation difficulty is reduced, and the balance relation between the mapping performance and the operation real-time performance does not need to be considered.

Description

technical field [0001] The invention relates to the field of positioning and mapping based on laser radar sensors, in particular to a multi-point cloud map fusion method and device based on offline global optimization. Background technique [0002] Since the Simultaneous Localization and Mapping (SLAM) problem was first proposed in 1985, SLAM technology has experienced more than 30 years of development, and its theoretical system has been basically improved; it has now entered the era of robust perception for specific applications , especially play an important role in the fields of mobile robots and unmanned driving, and a large number of SLAM methods with excellent performance continue to emerge. [0003] In the process of unmanned vehicles performing specific tasks, the prior point cloud map used for matching and positioning is an integral part of the entire algorithm module, and the point cloud map can be obtained through the existing mature laser SLAM method. However, ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/00G01S17/86G01S17/89
Inventor 华炜高海明张顺胡艳明马也驰邱奇波
Owner ZHEJIANG LAB
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