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mid360 yaml配置问题 #93

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batmelody opened this issue Jan 25, 2024 · 2 comments
Open

mid360 yaml配置问题 #93

batmelody opened this issue Jan 25, 2024 · 2 comments

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@batmelody
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batmelody commented Jan 25, 2024

common:
lid_topic: "/livox/lidar"
imu_topic: "/mavros/imu/data_raw"

preprocess:
lidar_type: 1 # Livox series LiDAR
feature_extract_en: false
scan_line: 6
blind: 1

initialization:
cut_frame_num: 5 # must be positive integer
orig_odom_freq: 10 # original Lidar frequency
mean_acc_norm: 9.805 # 1 for livox built-in IMU
online_refine_time: 20 # seconds
data_accum_length: 500
Rot_LI_cov: [ 0.00005, 0.00005, 0.00005 ]
Trans_LI_cov: [ 0.00001, 0.00001, 0.00001 ]

mapping:
filter_size_surf: 0.05
filter_size_map: 0.15
gyr_cov: 50
acc_cov: 2
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
det_range: 100.0

publish:
path_en: true
scan_publish_en: true # false: close all the point cloud output
dense_publish_en: true # false: low down the points number in a global-frame point clouds scan.
scan_bodyframe_pub_en: false # true: output the point cloud scans in IMU-body-frame

pcd_save:
pcd_save_en: false
interval: -1 # how many LiDAR frames saved in each pcd file;
# -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.

您好,我使用的激光雷达是mid360,这是我截取您yaml文件里的配置。这里的acc_cov与gyr_cov是否过大了。还有其它值是否有什么需要修改的?

@zfc-zfc
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zfc-zfc commented Jan 26, 2024

common: lid_topic: "/livox/lidar" imu_topic: "/mavros/imu/data_raw"

preprocess: lidar_type: 1 # Livox series LiDAR feature_extract_en: false scan_line: 6 blind: 1

initialization: cut_frame_num: 5 # must be positive integer orig_odom_freq: 10 # original Lidar frequency mean_acc_norm: 9.805 # 1 for livox built-in IMU online_refine_time: 20 # seconds data_accum_length: 500 Rot_LI_cov: [ 0.00005, 0.00005, 0.00005 ] Trans_LI_cov: [ 0.00001, 0.00001, 0.00001 ]

mapping: filter_size_surf: 0.05 filter_size_map: 0.15 gyr_cov: 50 acc_cov: 2 b_acc_cov: 0.0001 b_gyr_cov: 0.0001 det_range: 100.0

publish: path_en: true scan_publish_en: true # false: close all the point cloud output dense_publish_en: true # false: low down the points number in a global-frame point clouds scan. scan_bodyframe_pub_en: false # true: output the point cloud scans in IMU-body-frame

pcd_save: pcd_save_en: false interval: -1 # how many LiDAR frames saved in each pcd file; # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.

您好,我使用的激光雷达是mid360,这是我截取您yaml文件里的配置。这里的acc_cov与gyr_cov是否过大了。还有其它值是否有什么需要修改的?

就是要很大,否则EKF本身的滤波器延迟会影响时差标定结果。其他 注意一下地图分辨率就好

@batmelody
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谢谢回复,当我使用一个很大的cov之后,我的标定建图会发生错层,抖动;把cov减小将恢复正常,请问这种情况下要如何去调整这个cov呢?

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