Comments (3)
Hi @HSarham ,
You can include gicp/impl/*_impl.hpp
to use the point types you want to use. You can also add them to fast_gicp.cpp
.
https://github.com/SMRT-AIST/fast_gicp/blob/master/src/fast_gicp/gicp/fast_gicp.cpp
from fast_gicp.
Hi ,
Have you use pcl::PointXYZRGBNormal? Did it work better?
Cheers
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Hi @aiai84 ,
You can feed any type of points to FastGICP, but it doesn't use any information other than XYZ coordinates.
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Related Issues (20)
- cmake error HOT 1
- lm not converged!! HOT 4
- about the parameter kCorrespondences HOT 4
- Yes, it is an approximated way; the covariances of source points are fixed at the linearization point and do not change during cost evaluation. I implemented an exact version with covariance drivatives, but it didn't improve accuracy nor stability while making optimization significantly slow. If you want, you can try it at the following link:
- Thank you for sharing. Can you give the detailed derivation process of Jacobi?
- Example of exporting results for evaluation? HOT 2
- VGICP_CUDA and NDT CUDA not work on Nvidia jetson HOT 2
- GICP vs VGICPCuda Performance Issue HOT 4
- NDTCuda "lm not converged!!" HOT 1
- [question] How would I go about optimizing < 6 pose parameters? HOT 3
- cuda stream HOT 8
- Compiling error HOT 2
- make in debug, eigen error HOT 1
- Crash while using VGICP
- how to take fast_gicp in my own code? HOT 3
- About NeighborSearchMethod HOT 1
- got "for_each: failed to synchronize" in every position using "thrust::for_each" HOT 2
- doc request: aligned output point cloud must be different from source and target HOT 1
- Registration score gradually diverges. HOT 3
- cudaErrorIllegalAddress: an illegal memory access was encountered HOT 1
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