Which hand eye calibration method is the most popular?
Hello, I spent some time looking for Implementations, that solve the Hand-Eye-Problem AX=XB. There are several repositories such as:
Is there a common and most used implementation? Which algorithm is state of the are and offers the best results? Where is its implementation?
Thanks for some hints
Nils
Asked by nmelchert on 2019-04-25 01:52:29 UTC
Comments
have you found out which is the best?
Asked by nd on 2019-06-06 08:38:16 UTC
Apparently the handeye_calib_camodocal package is base on this paper leads to the most robust results.
I would love to have a python implementation of that algroithm, but have not found any implementations yet.
Asked by nmelchert on 2019-06-06 09:21:17 UTC
easy_handeye worked well for me for calibrating the rotation of a Structure Core camera mounted on the wrist of a ur5 robot. However, the translation is off by a few centimeters. Tested over multiple runs and AR markers with different shapes and sizes.
Asked by atp on 2019-11-20 11:22:05 UTC
A few centimeters is a pretty big difference. Your camera calibration could be the cause of this deviation.
Asked by nmelchert on 2019-11-20 13:10:22 UTC
I was just searching information on that and I found that question quite useful! Just to add that if you want to use Ensenso, they have their own implementation in the official API.
Asked by Solrac3589 on 2020-03-02 10:55:17 UTC
Well, but what kind of algorithm do they use?
Asked by nmelchert on 2020-03-02 10:57:14 UTC
No idea. I am using just the API. I think the backend it's not open source, but I tought was going to work optimally in the case.
Asked by Solrac3589 on 2020-03-09 08:20:45 UTC