How example "Perform SLAM Using 3D lidar point clouds"collects 3D lidar data?ud
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Wenjun Li
el 16 de Feb. de 2022
Comentada: Wenjun Li
el 18 de Feb. de 2022
When I was learning this routine, I didn't know how to collect the 3D Lidar data. Is it a 1*240 cell array formed by scanning 240 instances and then extracting their location attributes?
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Ryan Salvo
el 16 de Feb. de 2022
Hi Wenjun,
For the Perform SLAM Using 3-D Lidar Point Clouds example, the lidar data stored in the pClouds MAT-file was collected on a Clearpath Husky robot moving around a parking garage. Each cell in the 1-by-240 cell array corresponds to a different timestep and each cell contains an n-by-3 matrix, where n is the number 3-D points in the captured lidar data, and the columns represent xyz-coordinates associated with each captured point.
Thanks,
Ryan
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Ryan Salvo
el 17 de Feb. de 2022
Hi Wenjun,
In the example, the lidar takes 240 successive scans, however, there is a varying number of points detected in each scan due to the number of obstacles in the immediate environment. That is why the scan for each timestep is logged in a different cell of the cell array. The scans take the same amount of time, however, successive scans are only accepted when the robot has moved a certain distance, specfied by the distanceMovedThreshold parameter.
Thanks,
Ryan
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Wenjun Li
el 18 de Feb. de 2022
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Ryan Salvo
el 18 de Feb. de 2022
Hi Wenjun,
You do not need 240 successive scans, that is just the number of scans in the MAT-file provided in the example.
The example assumes that the provided lidar data is from a robot that is moving through a static space, so if you can re-create that when recording the BAG-file, then you should be able to use that data with the example.
Thanks,
Ryan
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