UditSinghParihar/README.md

Last active September 5, 2019 01:57

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g2o optmization on second half of dataset 1

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    Following are the results of dataset1's second half optimization, using manhattan constraints.

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UditSinghParihar commented Sep 5, 2019 •

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Dense ground truth trajectory.
Dense noisy trajectory, with its first pose aligned with first pose of optimized trajectory to remove the rotation effect.
Manhattan sparse trajectory.
G2o optmization is done using Cauchy algorithm with kernel width = 1.0 . All the manhattan constraints are given with respect to the first node. Left: Unoptimized and Right: Optimized.
Comparison of noisy, optimized and ground truth trajectory. Note that the first pose of all three trajectories are overlapping which avoids rotation effect.

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