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koide3 avatar koide3 commented on August 25, 2024

Sorry, I have been apart from g2o for a few years, and I'm not sure the exact way to implement the proposed approach with g2o. But, in my case with GTSAM, I implemented a custom GICP registration error factor with gtsam::NonlinearFactor that returns a linearized objective function as gtsam::HessianFactor. The following page explains in detail what do H, b, c (corresponding to G, g, f) in the HessianFactor represent. I hope this helps you.

https://gtsam.org/doxygen/a03764.html

from caratheodory2.

Kenzo2511 avatar Kenzo2511 commented on August 25, 2024

Thank you for your answer. You means that I will create a GicpFactor class inherited from gtsam::NonlinearFactor and modify the linearize and error method and returns a gtsam::HessianFactor with H, b, c calculated within the error function (GICP score).
Do I need to modify the error method in GicpFactor or inheritance from gtsam::NonlinearFactor?
image (3)
H corresponds to G, b corresponds to g, and c corresponds to f.
Looking forward to hearing from you soon. Thank you very much.

from caratheodory2.

koide3 avatar koide3 commented on August 25, 2024

You are almost correct. You need to GICPFactor that is derived from gtsam::NonlinearFactor. That factor class should override gtsam::NonlinearFactor::linearize to return a gtsam::HessianFactor. Because GICPFactor involves two pose variables, you would need to use this HessianFactor constructor. H, b, and c respectively correspond to G, g, f.

Screenshot_20231225_110343
https://gtsam.org/doxygen/a03764.html#abb07c3bd55ff688700f82f6024bdf9f0

from caratheodory2.

Kenzo2511 avatar Kenzo2511 commented on August 25, 2024

Thank you, I understand. However, to ensure the idea, I want to confirm the following two questions:

  • Do H, b, c in GICPFactor::linearize represent H, b, c after applying GICP to two point clouds (final iteration) or not? (Could you please explain this question to me clearly?)
  • GICPFactor::error will be computed as follows, right? 0.5∗x′Gx−x′∗g+0.5∗f
    Looking forward to hearing from you soon. Thank you very much.

from caratheodory2.

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