问题
I´m trying to align 2 sets of point clouds using the Iterative Closest Point (ICP) algorithm integrated within Point Cloud Library (PCL). I´m getting an error report saying that it cant find enough correspondence points. I have already relaxed the conditions for the parameters: setEuclideanFitnessEpsilon(-1.797e+5), setMaximumIterations(40) and setRANSACIterations(2000) and still having the same problem.. (I havent found much info about which or how these conditional values should be for a proper alignement, so any help in this regard would be really appreciated too)
I´m suspecting that this problem has to do with the fact that I have many NULL data points in my cloud, which I´ve marked with the value NULL (0). Is that properly done when using PCL? Is there any NULL standard value for PCL? I clearly dont want the algorithm to consider those NULL points when trying to align the data sets..
Thanks for your help
回答1:
If you are using PCL, default value of invalid data is not NULL, but is NaN. So if you want to mark a point as invalid, you should first include <limits>
file and then set the positions to 'std::numeric_limits::quiet_NaN()'. It is usually done like this
const float bad_point = std::numeric_limits<float>::quiet_NaN();
if( is_invalid_point )
p.x = p.y = p.z = bad_point;
But anyway, configuring ICP can be a pain. You may have to do a lot more parameter tweaking depending on your data.
来源:https://stackoverflow.com/questions/17281470/how-to-mark-null-data-in-point-cloud-library-pcl-when-using-iterative-closest