CN-122017869-A - Fusion method, device, equipment and medium of IGV multi-laser radar point cloud

CN122017869ACN 122017869 ACN122017869 ACN 122017869ACN-122017869-A

Abstract

The invention relates to the technical field of point cloud data, in particular to a fusion method, a device, equipment and a medium of IGV multi-laser radar point clouds, wherein the fusion method comprises the steps of acquiring original point cloud data acquired by a plurality of laser radars and inertial measurement data measured by an inertial measurement unit; the method comprises the steps of keeping the time stamps of a plurality of laser radars consistent with those of an inertial measurement unit, carrying out de-distortion on original point cloud data based on the inertial measurement data to obtain first point cloud data, converting a laser radar coordinate system corresponding to each frame of the first point cloud data into an IGV vehicle body coordinate system, obtaining second point cloud data after fusion, carrying out self-adaptive downsampling and impurity point filtering on the second point cloud data to obtain third point cloud data, calculating actual generation time according to the scanning speed and the scanning angle of the laser radars corresponding to each point cloud in the third point cloud data, and sequencing the third point cloud data according to the actual generation time to obtain fused point cloud data. The invention can obtain more accurate and stable point cloud data.

Inventors

MA ZHIJIAN
ZHAO BIN
HUANG ZHIWEI
Zou Haozhong
KANG HONGYI
LU JUNGUO
ZHANG QINGHAO

Assignees

上海振华重工集团科技有限公司
上海振华重工(集团)股份有限公司
上海交通大学

Dates

Publication Date: 20260512
Application Date: 20260402

Claims (10)

1. An IGV multi-laser radar point cloud fusion method, characterized in that the IGV is provided with an inertial measurement unit and a plurality of laser radars, and the sum of scanning ranges of the plurality of laser radars covers the periphery and the upper part of the IGV, the fusion method comprising: acquiring original point cloud data acquired by each of a plurality of laser radars and inertial measurement data measured by an inertial measurement unit, wherein the time stamps of the plurality of laser radars and the inertial measurement unit are kept consistent; performing de-distortion processing on the original point cloud data corresponding to each laser radar based on the inertial measurement data to obtain first point cloud data; Converting a laser radar coordinate system corresponding to the first point cloud data of each frame into a vehicle body coordinate system of the IGV, and fusing all the converted first point cloud data to obtain second point cloud data; Performing self-adaptive downsampling and clutter filtering on the second point cloud data to obtain third point cloud data; Calculating the actual generation time of each point cloud according to the scanning speed and the current scanning angle of the laser radar corresponding to each point cloud in the third point cloud data, and reordering the third point cloud data according to the actual generation time corresponding to each point cloud to obtain the fusion point cloud data of the multi-laser radar.
2. The IGV multi-laser radar point cloud fusion method of claim 1, wherein performing de-distortion processing on the raw point cloud data corresponding to each of the laser radars based on the inertial measurement data to obtain the first point cloud data comprises: the inertial measurement data comprise acceleration data and angular velocity data, and dead reckoning is carried out by utilizing the acceleration data and the angular velocity data to obtain an IGV motion pose corresponding to the original point cloud data; And adjusting the motion deviation of the original point cloud data according to the IGV motion pose to obtain the first point cloud data.
3. The method of claim 1, wherein converting the lidar coordinate system corresponding to each frame of the first point cloud data into the vehicle body coordinate system of the IGV comprises: calculating a rotation matrix and a translation vector of each laser radar coordinate system relative to the vehicle body coordinate system; and applying the rotation matrix and the translation vector to the corresponding first point cloud data to complete coordinate system conversion.
4. The method of merging the IGV multiple laser radar point clouds of claim 1, wherein adaptively downsampling the second point cloud data comprises adaptively downsampling the second point cloud data using a voxel grid filter algorithm.
5. The method for merging the point clouds of the IGV multi-laser radar according to claim 4, wherein a voxel grid filter algorithm is adopted to divide a point cloud space corresponding to the second point cloud data into a plurality of voxels, the voxel size of the corresponding region is adjusted according to the point cloud density of each region in the point cloud space, and the voxel size is inversely proportional to the point cloud density.
6. The IGV multi-laser radar point cloud fusion method of claim 1, wherein calculating an actual generation time of each point cloud according to a scanning speed of the laser radar corresponding to each point cloud in the third point cloud data and a scanning angle at the time comprises: acquiring the time stamp time of each point cloud in the third point cloud data; calculating the time deviation corresponding to each point cloud according to the scanning speed of the laser radar corresponding to each point cloud and the scanning angle at the moment; and obtaining the actual generation time of each point cloud based on the time deviation and the time stamp time corresponding to each point cloud.
7. The method of merging IGV multi-lidar point clouds according to claim 1, wherein said method of keeping a plurality of said lidars in agreement with the time stamps of said inertial measurement unit comprises network time protocol, precision time protocol or GPS signal synchronization.
8. An IGV multi-laser radar point cloud fusion device, characterized in that, the IGV is provided with inertial measurement unit and a plurality of laser radars, a plurality of the sum of laser radars' scanning range covers IGV all around and the top, the fusion device includes: The data acquisition module is used for acquiring original point cloud data acquired by each of the plurality of laser radars and inertial measurement data measured by the inertial measurement unit, wherein the time stamps of the plurality of laser radars and the inertial measurement unit are kept consistent; The de-distortion processing module is used for performing de-distortion processing on the original point cloud data corresponding to each laser radar based on the inertial measurement data to obtain first point cloud data; the coordinate system conversion module is used for converting a laser radar coordinate system corresponding to each frame of the first point cloud data into a vehicle body coordinate system of the IGV, and fusing all converted first point cloud data to obtain second point cloud data; the downsampling and filtering module is used for carrying out self-adaptive downsampling and impurity point filtering on the second point cloud data to obtain third point cloud data; The system comprises a third point cloud data acquisition module, a point cloud time sequencing module and a multi-laser radar fusion point cloud data acquisition module, wherein the third point cloud data acquisition module is used for acquiring the third point cloud data according to the scanning speed of the laser radar corresponding to each point cloud in the third point cloud data and the scanning angle at the moment, calculating the actual generation time of each point cloud, and re-sequencing the third point cloud data according to the actual generation time corresponding to each point cloud.
9. An electronic device comprising a processor and a memory, wherein the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program loaded and executed by the processor to implement the IGV multi-laser radar point cloud fusion method of any of claims 1-7.
10. A computer readable storage medium having stored therein at least one instruction or at least one program loaded and executed by a processor to implement the IGV multi-laser radar point cloud fusion method of any of claims 1-7.

Description

Fusion method, device, equipment and medium of IGV multi-laser radar point cloud Technical Field The invention relates to the technical field of point cloud data, in particular to a fusion method, a device, equipment and a medium of an IGV multi-laser radar point cloud. Background With the development of automated docks, intelligent Guided Vehicles (IGVs) become core transportation devices, the reliability of their autonomous navigation is highly dependent on accurate real-time perception of the surrounding environment. Lidar has become the mainstream sensor for IGV environmental awareness due to its high accuracy and non-illumination-affected characteristics. However, single lidar has inherent blind view, especially in the near-body region and directly in front of or behind the vehicle, often obscured by the vehicle body or container. To solve this problem, multi-lidar fusion is a viable solution. However, the data of different lidars have the problems of time asynchronism and independent coordinate systems. Directly fusing point cloud data which is not synchronously processed can cause motion distortion and time dislocation, so that the accuracy of subsequent processing is reduced. At the same time, the large amount of unordered fusion point cloud data can also affect the real-time processing capabilities of the computing system. Therefore, there is a need for a multi-lidar fusion system that is suitable for the characteristics of the IGV working environment of dock operations, to achieve comprehensive environmental awareness, ensure time-space synchronization at the data level, output stable and precisely located environmental expression data. Disclosure of Invention Aiming at the problems in the prior art, the invention aims to provide a fusion method, a device, equipment and a medium of IGV multi-laser radar point clouds, which can solve the problem that the positioning accuracy is affected by the point cloud data obtained by fusion of the multi-laser radars due to motion distortion and time dislocation. In order to solve the problems, the invention adopts the following technical scheme: According to a first aspect of the present invention, there is provided a fusion method of an IGV multi-laser radar point cloud, the IGV being provided with an inertial measurement unit and a plurality of laser radars, a sum of scanning ranges of the plurality of laser radars covering around and above the IGV, the fusion method comprising: acquiring original point cloud data acquired by each of a plurality of laser radars and inertial measurement data measured by an inertial measurement unit, wherein the time stamps of the plurality of laser radars and the inertial measurement unit are kept consistent; performing de-distortion processing on the original point cloud data corresponding to each laser radar based on the inertial measurement data to obtain first point cloud data; Converting a laser radar coordinate system corresponding to each frame of first point cloud data into an IGV vehicle body coordinate system, and fusing all converted first point cloud data to obtain second point cloud data; performing self-adaptive downsampling and clutter filtering on the second point cloud data to obtain third point cloud data; Calculating the actual generation time of each point cloud according to the scanning speed and the current scanning angle of the laser radar corresponding to each point cloud in the third point cloud data, and reordering the third point cloud data according to the actual generation time corresponding to each point cloud to obtain the fusion point cloud data of the multi-laser radar. In some embodiments, performing de-distortion processing on original point cloud data corresponding to each laser radar based on inertial measurement data to obtain first point cloud data, including: The inertial measurement data comprise acceleration data and angular velocity data, and dead reckoning is carried out by utilizing the acceleration data and the angular velocity data to obtain an IGV motion pose corresponding to the original point cloud data; and adjusting the motion deviation of the original point cloud data according to the IGV motion pose to obtain first point cloud data. In some embodiments, converting a lidar coordinate system corresponding to each frame of first point cloud data to an IGV vehicle body coordinate system includes: Calculating a rotation matrix and a translation vector of each laser radar coordinate system relative to a vehicle body coordinate system; and applying the rotation matrix and the translation vector to the corresponding first point cloud data to complete coordinate system conversion. In some embodiments, adaptively downsampling the second point cloud data includes adaptively downsampling the second point cloud data using a voxel grid filter algorithm. In some embodiments, a voxel grid filter algorithm is used to divide the point cloud space corresponding to the second point cloud data