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feat(slam): add lidar SLAM and pointcloud processing packages

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X-lanni
2026-01-13 19:12:25 +08:00
parent dcb52622eb
commit ddef31d11a
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FAST_LIO/config/avia.yaml
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/**:
ros__parameters:
feature_extract_enable: false
point_filter_num: 3
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 1000.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
common:
lid_topic: "/livox/lidar"
imu_topic: "/livox/imu"
time_sync_en: false # ONLY turn on when external time synchronization is really not possible
time_offset_lidar_to_imu: 0.0 # Time offset between lidar and IMU calibrated by other algorithms, e.g. LI-Init (can be found in README).
# This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
preprocess:
lidar_type: 1 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
scan_line: 6
blind: 4.0
mapping:
acc_cov: 0.1
gyr_cov: 0.1
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
fov_degree: 90.0
det_range: 450.0
extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic
extrinsic_T: [ 0.04165, 0.02326, -0.0284 ]
extrinsic_R: [ 1., 0., 0.,
0., 1., 0.,
0., 0., 1.]
publish:
path_en: false
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: true # true: output the point cloud scans in IMU-body-frame
pcd_save:
pcd_save_en: true
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.
FAST_LIO/config/horizon.yaml
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/**:
ros__parameters:
feature_extract_enable: false
point_filter_num: 3
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 1000.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
common:
lid_topic: "/livox/lidar"
imu_topic: "/livox/imu"
time_sync_en: false # ONLY turn on when external time synchronization is really not possible
time_offset_lidar_to_imu: 0.0 # Time offset between lidar and IMU calibrated by other algorithms, e.g. LI-Init (can be found in README).
# This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
preprocess:
lidar_type: 1 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
scan_line: 6
blind: 4.0
mapping:
acc_cov: 0.1
gyr_cov: 0.1
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
fov_degree: 100.0
det_range: 260.0
extrinsic_est_en: true # true: enable the online estimation of IMU-LiDAR extrinsic
extrinsic_T: [ 0.05512, 0.02226, -0.0297 ]
extrinsic_R: [ 1., 0., 0.,
0., 1., 0.,
0., 0., 1.]
publish:
path_en: false
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: true # true: output the point cloud scans in IMU-body-frame
pcd_save:
pcd_save_en: true
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.
FAST_LIO/config/mid360.yaml
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/**:
ros__parameters:
feature_extract_enable: false
point_filter_num: 3
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 400.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
common:
lid_topic: "/livox/lidar"
imu_topic: "/livox/imu"
time_sync_en: false # ONLY turn on when external time synchronization is really not possible
time_offset_lidar_to_imu: 0.0 # Time offset between lidar and IMU calibrated by other algorithms, e.g. LI-Init (can be found in README).
# This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
preprocess:
lidar_type: 1 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR, 4 for any other pointcloud input
scan_line: 4
blind: 0.5
timestamp_unit: 3
scan_rate: 10
mapping:
acc_cov: 0.1
gyr_cov: 0.1
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
fov_degree: 360.0
det_range: 60.0
extrinsic_est_en: true # true: enable the online estimation of IMU-LiDAR extrinsic
extrinsic_T: [ -0.011, -0.02329, 0.04412 ]
extrinsic_R: [ 1., 0., 0.,
0., 1., 0.,
0., 0., 1.]
publish:
path_en: true # true: publish Path
effect_map_en: true # true: publish Effects
map_en: true # true: publish Map cloud
scan_publish_en: true # false: close all the point cloud output
dense_publish_en: false # false: low down the points number in a global-frame point clouds scan.
scan_bodyframe_pub_en: true # true: output the point cloud scans in IMU-body-frame
pcd_save:
pcd_save_en: true
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.
FAST_LIO/config/ouster64.yaml
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/**:
ros__parameters:
feature_extract_enable: false
point_filter_num: 3
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 1000.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
common:
lid_topic: "/os_cloud_node/points"
imu_topic: "/os_cloud_node/imu"
time_sync_en: false # ONLY turn on when external time synchronization is really not possible
time_offset_lidar_to_imu: 0.0 # Time offset between lidar and IMU calibrated by other algorithms, e.g. LI-Init (can be found in README).
# This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
preprocess:
lidar_type: 3 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
scan_line: 64
timestamp_unit: 3 # 0-second, 1-milisecond, 2-microsecond, 3-nanosecond.
blind: 4.0
mapping:
acc_cov: 0.1
gyr_cov: 0.1
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
fov_degree: 360.0
det_range: 150.0
extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic
extrinsic_T: [ 0.0, 0.0, 0.0 ]
extrinsic_R: [1., 0., 0.,
0., 1., 0.,
0., 0., 1.]
publish:
path_en: false
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: true # true: output the point cloud scans in IMU-body-frame
pcd_save:
pcd_save_en: true
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.
FAST_LIO/config/unilidar_l2.yaml
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/**:
ros__parameters:
# ================== Global Settings ==================
feature_extract_enable: false
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 1000.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
# ================== Sensor Topics ==================
common:
lid_topic: "/unilidar/cloud" # LiDAR点云话题
imu_topic: "/unilidar/imu" # IMU话题
time_sync_en: false # 关闭内部时间同步（若需要同步请设为true）
time_offset_lidar_to_imu: 0.0 # IMU到LiDAR时间偏移（与您配置的time_lag_imu_to_lidar取反）
# ================== LiDAR预处理 ==================
preprocess:
lidar_type: 5 # 雷达类型（需确认类型编号对应关系）
scan_line: 18 # 扫描线数
point_filter_num: 1 # 点云降采样率（原con_frame_num）
blind: 0.5 # 盲区过滤半径（米）
timestamp_unit: 0 # 时间戳单位：0=秒，1=毫秒，2=微秒，3=纳秒
# ================== SLAM核心参数 ==================
mapping:
# IMU参数
imu_en: true # 启用IMU
imu_time_inte: 0.004 # IMU采样间隔（1/frequency）
acc_cov: 0.1 # 加速度计噪声协方差
gyr_cov: 0.1 # 陀螺仪噪声协方差
b_acc_cov: 0.0001 # 加速度计零偏噪声
b_gyr_cov: 0.0001 # 陀螺仪零偏噪声
# 外参标定
extrinsic_est_en: false # 关闭在线外参标定
extrinsic_T: [0.007698, 0.014655, -0.00667] # IMU到LiDAR平移
extrinsic_R: [1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0] # IMU到LiDAR旋转矩阵
# 环境参数
fov_degree: 180.0 # 有效FOV角度
det_range: 100.0 # 最大探测距离（米）
plane_thr: 0.1 # 平面拟合阈值
# 重力对齐
gravity_align: true # 启用重力对齐
gravity: [0.0, 0.0, -9.810] # 重力向量（与您配置一致）
# ================== 输出设置 ==================
publish:
path_en: true # 发布轨迹路径
scan_publish_en: true # 发布原始点云
scan_bodyframe_pub_en: true # 发布IMU坐标系点云
dense_publish_en: true # 发布稠密地图
# ================== 地图保存 ==================
pcd_save:
pcd_save_en: true # 启用PCD保存
interval: -1 # 全帧保存（注意内存风险）
FAST_LIO/config/velodyne.yaml
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/**:
ros__parameters:
feature_extract_enable: false
point_filter_num: 4
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5
cube_side_length: 1000.0
runtime_pos_log_enable: false
map_file_path: "./test.pcd"
common:
lid_topic: "/velodyne_points"
imu_topic: "/imu/data"
time_sync_en: false # ONLY turn on when external time synchronization is really not possible
time_offset_lidar_to_imu: 0.0 # Time offset between lidar and IMU calibrated by other algorithms, e.g. LI-Init (can be found in README).
# This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
preprocess:
lidar_type: 2 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
scan_line: 32
scan_rate: 10 # only need to be set for velodyne, unit: Hz,
timestamp_unit: 2 # the unit of time/t field in the PointCloud2 rostopic: 0-second, 1-milisecond, 2-microsecond, 3-nanosecond.
blind: 2.0
mapping:
acc_cov: 0.1
gyr_cov: 0.1
b_acc_cov: 0.0001
b_gyr_cov: 0.0001
fov_degree: 360.0
det_range: 100.0
extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic,
extrinsic_T: [ 0., 0., 0.28]
extrinsic_R: [ 1., 0., 0.,
0., 1., 0.,
0., 0., 1.]
publish:
path_en: false
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: true # true: output the point cloud scans in IMU-body-frame
pcd_save:
pcd_save_en: true
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.