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Comments (2)

gisbi-kim avatar gisbi-kim commented on August 14, 2024

no particular reason for that :)
but I just wanna use a slightly larger value than the original repo,
because I found some actually true loops sometimes have ~1 fitness scores so I didn't wanna miss those loops.

If wrong loop factors occured, it's okay because we use a robust kernel for loop factors,
(see below lines)

gtsam::noiseModel::mEstimator::Cauchy::Create(1), // optional: replacing Cauchy by DCS or GemanMcClure, but with a good front-end loop detector, Cauchy is empirically enough.

so we can reduce those wrong loops effects when enough true loops exist.

ps. empirically, I tested the harshest cases where the number of wrong loops was maximized when the scan context descriptor threshold = 1.0 (i.e., all loops were accepted). below is the result and the trajectory still looks good.

cauchy_good1

from sc-lio-sam.

Xiangzhaohong avatar Xiangzhaohong commented on August 14, 2024

ok!thanks !
I just noticed that your video have many loops in the begining , but the results is good!
image

from sc-lio-sam.

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