Comments (3)
I would suggest reading GTSAM tutorial on how to represent 2D landmarks and add corresponding contraints: https://gtsam.org/tutorials/intro.html#magicparlabel-65635
In my case, I represented landmark also as VERTEX_SE3
for 6DOF object pose. In https://itzsid.github.io/publications/Cieslewski18icra.pdf, we didn't optimize landmarks, it was a pose graph optimization.
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Hi @Quest2GM, If a landmark is represented using 6DOF pose (e.g. 3D object poses), then in the current setup you can represent the landmark in the same way as robot pose using VERTEX_SE3
. Intra-robot edges can represent robot-landmark constraints as well along with odometry constraints.
However, if landmark type is different from VERTEX_SE3, then the corresponding G2o file has to be updated and the factor graph needs to have the appropriate constraints. It won't affect the distributed mapping component since the inter-robot constraints are between robot poses and not landmarks.
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Can you clarify what you mean by "the corresponding G2o file has to be updated and the factor graph needs to have appropriate constraints?". If, for example, our landmark type was VERTEX_SE2,
then exactly what updates need to be made to the g2o file, and what would a constraint look like?
Also, how did you achieve landmark optimization in your paper? Did you use VERTEX_SE3
landmarks as you describe above?
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