Drone lidar mapping data process
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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
on 23 Jul 2024
Edited: Umar
on 23 Jul 2024
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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