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Termination: NO_CONVERGENCE on my own dataset #46
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Hi again ! So, the NO_CONVERGENCE should not necessarily be a problem. Indeed, we limit the number of iterations of the optimizer during the ICP, in order to speed up computations. For the optimal parameters of the OS-128, it depends what is your goal accuracy or speed ? I am curious about your results, does it work well with the default parameters or do you have failures ? Note that we do a sampling of the frame and of keypoints in this frame, which should help with the massive data from the os-128. |
Hi. Thanks for your detailed reply! |
For accuracy you should use the config Note that the default config is really specialized for driving scenarios, and will not work at all for indoor (whereas |
Indeed, my dataset is collected in an underground indoor parking lot. |
I have tried the OS-128 config and tuned keypoints num and voxel size. Thanks! |
Hi Thanks for your sharing of this excellent work!
I have ssuccessfully run ct icp on my own dataset, however, I have two question, and I hope you can help me!
(1) My dataset is collected using OS1-128 Lidar, shoud I modified any configuration in the code to adapt to the lidar?
(2) The terminal says : Termination: NO_CONVERGENCE, Is it normal? Or did I mistake something? I have post one output below, the loss is about 0.1.
Thanks for your reading!
/* ------------------------------------------------------------------------ */
REGISTRATION OF FRAME number 704 (Fid:704) with CERES solver
Number of points in sub-sampled frame: 6292
Initial ego-motion distance: 0.219946
Ceres Solver Report: Iterations: 2, Initial cost: 1.823143e-01, Final cost: 1.734975e-01, Termination: NO_CONVERGENCE
[CT-ICP]: Rotation diff: 0.25545(deg)
[CT-ICP]: Translation diff: 0.0268903(m)
Ceres Solver Report: Iterations: 2, Initial cost: 1.753664e-01, Final cost: 1.741726e-01, Termination: NO_CONVERGENCE
[CT-ICP]: Rotation diff: 0.126741(deg)
[CT-ICP]: Translation diff: 0.0156516(m)
Ceres Solver Report: Iterations: 2, Initial cost: 1.658873e-01, Final cost: 1.649816e-01, Termination: NO_CONVERGENCE
[CT-ICP]: Rotation diff: 0.064464(deg)
[CT-ICP]: Translation diff: 0.0102195(m)
Ceres Solver Report: Iterations: 2, Initial cost: 1.587869e-01, Final cost: 1.583586e-01, Termination: NO_CONVERGENCE
[CT-ICP]: Rotation diff: 0.0440787(deg)
[CT-ICP]: Translation diff: 0.00744236(m)
Ceres Solver Report: Iterations: 2, Initial cost: 1.574686e-01, Final cost: 1.567192e-01, Termination: NO_CONVERGENCE
[CT-ICP]: Rotation diff: 0.0759043(deg)
[CT-ICP]: Translation diff: 0.00731901(m)
[CT-ICP]: Correction (Optim-Init[end])=0.0200416(m)
[CT-ICP]: Correction (Optim-Init[begin])=0.0105974(m)
[CT-ICP]: Begin Pose:
-0.372328 0.927865 0.0209494 9.44271
-0.927987 -0.372542 0.00730528 54.7062
0.0145828 -0.0167208 0.999754 -0.100985
0 0 0 1
[CT-ICP]: End Pose:
-0.371037 0.928334 0.0229463 9.35357
-0.928504 -0.371265 0.00648589 54.5304
0.0145402 -0.0188992 0.999716 -0.0981214
0 0 0 1
Trajectory correction [begin(t) - end(t-1)]: 0
Final ego-motion distance: 0.197156
Elapsed Time: 63.3284 (ms)
Inserting points in the Map: Skipped Frames [0 / 5] Total Insertions: 704
Cumulative Orientation: 0.117865°
Cumulative Distance: 0.18717m
Ego Orientation: 0.147157°
[RUNNING] Bag Time: 1656034744.789619 Duration: 70.598759 / 114.797567
[CT-ICP] Logged Values:
-- icp_duration_neighborhood: 32.8843
-- icp_duration_solve: 21.011
-- icp_num_iters: 5
-- icp_total_duration: 55.9733
-- odometry_duration_sampling: 0.164952
-- odometry_initialization: 0.720628
-- odometry_initialization(ms): 6.28906
-- odometry_map_update(ms): 37.0534
-- odometry_num_keypoints: 1045
-- odometry_total: 104.93
-- odometry_total_duration(ms): 63.3284
-- odometry_transform(ms): 3.43219
-- odometry_try_register: 57.0291
[RUNNING] Bag Time: 1656034744.839663 Duration: 70.648802 / 114.797567
/* ------------------------------------------------------------------------ */
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