Drone lidar mapping data process

Imre

2024 7 22

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Hi guys, I have a velodyne lidar (PCAP file) and a Neo-m8t gps (UBX) and Xsens MTI INS (csv file from ros2 bag), base station (RINEX). All sensor syncronised with timestamp, all have GPS coordinates. How can I process a 3D point cloud from them?

Thank you for your answers.

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Umar 2024-7-23

编辑：Umar 2024-7-23

Hi Imre ,

So, if your data is synchronized, you can combine the GPS coordinates from the sensors to create a 3D point cloud using this example,

% Combine GPS coordinates from sensors

combinedData = [lidarData.GPS_Coordinates, xsensData.GPS_Coordinates];

% Create a 3D point cloud

ptCloud = pointCloud(combinedData);

For more information on this function, please refer to https://www.mathworks.com/help/vision/ref/pointcloud.html

If you want to visualize the 3D point cloud then you can use cloud visualization functions like pcshow. This will allow you to inspect and analyze the combined data in a 3D space.

% Visualize the 3D point cloud

figure;

pcshow(ptCloud);

xlabel('X');

ylabel('Y');

zlabel('Z');

title('Combined 3D Point Cloud');

For more information on pcshow function, please refer to https://www.mathworks.com/help/vision/ref/pcshow.html?s_tid=doc_ta

By following these steps and using MATLAB's powerful data processing and visualization capabilities, you can effectively process a 3D point cloud from multiple synchronized sensors.

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