common: lid_topic: /points_raw #"/velodyne_points" imu_topic: /imu_raw #"/imu/data" time_sync_en: false # ONLY turn on when external time synchronization is really not possible #NCLT # lid_topic: "/points_raw" # imu_topic: "/imu_raw" #KITTI # lid_topic: "/kitti/velo/pointcloud" # imu_topic: "/kitti/oxts/imu" #RS LiDar # lid_topic: "/rslidar" # imu_topic: "/imu" preprocess: lidar_type: 2 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR, scan_line: 64 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: 1 mapping: acc_cov: 3.9939570888238808e-03 gyr_cov: 1.5636343949698187e-03 b_acc_cov: 6.4356659353532566e-05 b_gyr_cov: 3.5640318696367613e-05 fov_degree: 180 det_range: 100.0 extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic, extrinsic_T: [ -8.086759e-01, 3.195559e-01, -7.997231e-01] extrinsic_R: [9.999976e-01, 7.553071e-04, -2.035826e-03, -7.854027e-04, 9.998898e-01, -1.482298e-02, 2.024406e-03, 1.482454e-02, 9.998881e-01] 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: 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. # voxel filter paprams odometrySurfLeafSize: 0.4 # default: 0.4 - outdoor, 0.2 - indoor mappingCornerLeafSize: 0.2 # default: 0.2 - outdoor, 0.1 - indoor mappingSurfLeafSize: 0.4 # default: 0.4 - outdoor, 0.2 - indoor # robot motion constraint (in case you are using a 2D robot) z_tollerance: 1000 # meters rotation_tollerance: 1000 # radians # CPU Params numberOfCores: 4 # number of cores for mapping optimization mappingProcessInterval: 0.15 # seconds, regulate mapping frequency # Surrounding map surroundingkeyframeAddingDistThreshold: 10 #1.0 # meters, regulate keyframe adding threshold surroundingkeyframeAddingAngleThreshold: 0.2 # radians, regulate keyframe adding threshold surroundingKeyframeDensity: 2.0 # meters, downsample surrounding keyframe poses surroundingKeyframeSearchRadius: 50.0 # meters, within n meters scan-to-map optimization (when loop closure disabled) # Loop closure loopClosureEnableFlag: false loopClosureFrequency: 1.0 # Hz, regulate loop closure constraint add frequency surroundingKeyframeSize: 50 # submap size (when loop closure enabled) historyKeyframeSearchRadius: 5 #1.5 # meters, key frame that is within n meters from current pose will be considerd for loop closure historyKeyframeSearchTimeDiff: 30.0 # seconds, key frame that is n seconds older will be considered for loop closure historyKeyframeSearchNum: 20 # number of hostory key frames will be fused into a submap for loop closure historyKeyframeFitnessScore: 0.5 # icp threshold, the smaller the better alignment # Visualization globalMapVisualizationSearchRadius: 1000.0 # meters, global map visualization radius globalMapVisualizationPoseDensity: 10 # meters, global map visualization keyframe density globalMapVisualizationLeafSize: 1.0 # meters, global map visualization cloud density # visual iktree_map visulize_IkdtreeMap: true # visual iktree_map recontructKdTree: true # Export settings savePCD: true # https://github.com/TixiaoShan/LIO-SAM/issues/3 savePCDDirectory: "/fast_lio_sam_ws/src/FAST_LIO_SAM/PCD/" # in your home folder, starts and ends with "/". Warning: the code deletes "LOAM" folder then recreates it. See "mapOptimization" for implementation