You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello, I ran into a problem with my own dataset that matX contains NAN elements after solving linear equation AX=B using cv::solve() function in extrinsic_refine.hpp, causing failure in optimizing extrinsic between base LiDAR and ref LiDAR.
I've checked and made sure that my input point cloud does not contain NAN elements, what are possible solution to this problem to keep the optimization process running, thank you!
The text was updated successfully, but these errors were encountered:
Hi @Nicky0325 , have you tried using different voxel sizes and eigen_ratio?
Please let me know if this issue remains. I plan to update the project code but I am pretty busy this week.
Thank you, this is exactly the case. I found that the feature map was not correct due to faulty configuration of these two parameters. Thank you for the hints and the update, much appreciation!
Hello, I ran into a problem with my own dataset that
matX
contains NAN elements after solving linear equation AX=B usingcv::solve()
function inextrinsic_refine.hpp
, causing failure in optimizing extrinsic between base LiDAR and ref LiDAR.I've checked and made sure that my input point cloud does not contain NAN elements, what are possible solution to this problem to keep the optimization process running, thank you!
The text was updated successfully, but these errors were encountered: