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I tested your refactoring code with r3live_dataset-hku_campus_seq_00.bag. I turned off the visualization and changed some parameters (ds_size, voxel_size and max_voxel_num). On this dataset, the average frame processing time is around 80 ms. While as shown in your paper, your method (segment=1, with marginalization) time is 49.7 s on the NYA01 (395 s). And the average frame processing time is around 13 ms. So is it normal for my test? Do you have any suggestions to speed up the processing time? Here is my CPU and parameter setting.
Hello, @kevin2431 !
Thanks for your open-sourced and excellent work!
I tested your refactoring code with r3live_dataset-hku_campus_seq_00.bag. I turned off the visualization and changed some parameters (ds_size, voxel_size and max_voxel_num). On this dataset, the average frame processing time is around 80 ms. While as shown in your paper, your method (segment=1, with marginalization) time is 49.7 s on the NYA01 (395 s). And the average frame processing time is around 13 ms. So is it normal for my test? Do you have any suggestions to speed up the processing time? Here is my CPU and parameter setting.
CPU
Intel® Core™ i7-14700K × 28
trajectory:
init_interval: 3e8
seg_interval: 4e7
seg_num: 3
kinematic_constrain: 2.0
init_pose_weight: 1e9
converge_thresh: 0.001
max_iterations: 25
mapping:
ds_size: 2.0
voxel_size: 1.0
max_voxel_num: 10
planer_thresh: 0.1
max_range: 120
min_range: 1
Thank you in advance for your help!
Best regards,
Weitong Wu
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