velodyne16.yaml 4.0 KB

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  1. common:
  2. lid_topic: "/velodyne_points"
  3. imu_topic: "/imu/data"
  4. #NCLT
  5. # lid_topic: "/points_raw"
  6. # imu_topic: "/imu_raw"
  7. #KITTI
  8. # lid_topic: "/kitti/velo/pointcloud"
  9. # imu_topic: "/kitti/oxts/imu"
  10. #RS LiDar
  11. # lid_topic: "/rslidar"
  12. # imu_topic: "/imu"
  13. time_sync_en: false # ONLY turn on when external time synchronization is really not possible
  14. preprocess:
  15. lidar_type: 2 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
  16. scan_line: 16
  17. scan_rate: 10 # only need to be set for velodyne, unit: Hz,
  18. blind: 1
  19. mapping:
  20. acc_cov: 0.1
  21. gyr_cov: 0.1
  22. b_acc_cov: 0.0001
  23. b_gyr_cov: 0.0001
  24. fov_degree: 180
  25. det_range: 100.0
  26. extrinsic_est_en: true # true: enable the online estimation of IMU-LiDAR extrinsic,
  27. extrinsic_T: [ 0, 0, 0.28]
  28. extrinsic_R: [ 1, 0, 0,
  29. 0, 1, 0,
  30. 0, 0, 1]
  31. publish:
  32. path_en: true
  33. scan_publish_en: true # false: close all the point cloud output
  34. dense_publish_en: false # false: low down the points number in a global-frame point clouds scan.
  35. scan_bodyframe_pub_en: false # true: output the point cloud scans in IMU-body-frame
  36. pcd_save:
  37. pcd_save_en: false
  38. interval: -1 # how many LiDAR frames saved in each pcd file;
  39. # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.
  40. # voxel filter paprams
  41. odometrySurfLeafSize: 0.2 # default: 0.4 - outdoor, 0.2 - indoor
  42. mappingCornerLeafSize: 0.2 # default: 0.2 - outdoor, 0.1 - indoor
  43. mappingSurfLeafSize: 0.2 # default: 0.4 - outdoor, 0.2 - indoor
  44. # robot motion constraint (in case you are using a 2D robot)
  45. z_tollerance: 1000 # meters
  46. rotation_tollerance: 1000 # radians
  47. # CPU Params
  48. numberOfCores: 4 # number of cores for mapping optimization
  49. mappingProcessInterval: 0.15 # seconds, regulate mapping frequency
  50. # Surrounding map
  51. surroundingkeyframeAddingDistThreshold: 1.0 # meters, regulate keyframe adding threshold
  52. surroundingkeyframeAddingAngleThreshold: 0.2 # radians, regulate keyframe adding threshold
  53. surroundingKeyframeDensity: 2.0 # meters, downsample surrounding keyframe poses
  54. surroundingKeyframeSearchRadius: 50.0 # meters, within n meters scan-to-map optimization (when loop closure disabled)
  55. # Loop closure
  56. loopClosureEnableFlag: true # use loopclousre or not
  57. loopClosureFrequency: 4.0 # Hz, regulate loop closure constraint add frequency
  58. surroundingKeyframeSize: 50 # submap size (when loop closure enabled)
  59. historyKeyframeSearchRadius: 1.5 # meters, key frame that is within n meters from current pose will be considerd for loop closure
  60. historyKeyframeSearchTimeDiff: 30.0 # seconds, key frame that is n seconds older will be considered for loop closure
  61. historyKeyframeSearchNum: 20 # number of hostory key frames will be fused into a submap for loop closure
  62. historyKeyframeFitnessScore: 0.3 # icp threshold, the smaller the better alignment
  63. # Visualization
  64. globalMapVisualizationSearchRadius: 1000.0 # meters, global map visualization radius
  65. globalMapVisualizationPoseDensity: 10 # meters, global map visualization keyframe density
  66. globalMapVisualizationLeafSize: 1.0 # meters, global map visualization cloud density
  67. # visual iktree_map
  68. visulize_IkdtreeMap: true
  69. # visual iktree_map
  70. recontructKdTree: true
  71. # Export settings
  72. locate_mode: true
  73. savePCD: true # https://github.com/TixiaoShan/LIO-SAM/issues/3
  74. savePCDDirectory: "/doc/ros_ws/map/vlp16" # in your home folder, starts and ends with "/". Warning: the code deletes "LOAM" folder then recreates it. See "mapOptimization" for implementation