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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.
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.
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?
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