avia.yaml 3.8 KB

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  1. common:
  2. lid_topic: "/livox/lidar"
  3. imu_topic: "/livox/imu"
  4. time_sync_en: false # ONLY turn on when external time synchronization is really not possible
  5. preprocess:
  6. lidar_type: 1 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
  7. scan_line: 6
  8. blind: 2
  9. mapping:
  10. acc_cov: 0.1
  11. gyr_cov: 0.1
  12. b_acc_cov: 0.0001
  13. b_gyr_cov: 0.0001
  14. fov_degree: 90
  15. det_range: 450.0
  16. extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic
  17. extrinsic_T: [ 0.04165, 0.02326, -0.0284 ]
  18. extrinsic_R: [ 1, 0, 0,
  19. 0, 1, 0,
  20. 0, 0, 1]
  21. publish:
  22. path_en: true
  23. scan_publish_en: true # false: close all the point cloud output
  24. dense_publish_en: false # false: low down the points number in a global-frame point clouds scan.
  25. scan_bodyframe_pub_en: false # true: output the point cloud scans in IMU-body-frame
  26. pcd_save:
  27. pcd_save_en: false
  28. interval: -1 # how many LiDAR frames saved in each pcd file;
  29. # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.
  30. # voxel filter paprams
  31. odometrySurfLeafSize: 0.1 # default: 0.4 - outdoor, 0.2 - indoor
  32. mappingCornerLeafSize: 0.1 # default: 0.2 - outdoor, 0.1 - indoor
  33. mappingSurfLeafSize: 0.4 # default: 0.4 - outdoor, 0.2 - indoor
  34. # robot motion constraint (in case you are using a 2D robot)
  35. z_tollerance: 1 # meters
  36. rotation_tollerance: 1 # radians
  37. # CPU Params
  38. numberOfCores: 4 # number of cores for mapping optimization
  39. mappingProcessInterval: 0.15 # seconds, regulate mapping frequency
  40. # Surrounding map
  41. surroundingkeyframeAddingDistThreshold: 1.0 # meters, regulate keyframe adding threshold
  42. surroundingkeyframeAddingAngleThreshold: 0.2 # radians, regulate keyframe adding threshold
  43. surroundingKeyframeDensity: 2.0 # meters, downsample surrounding keyframe poses
  44. surroundingKeyframeSearchRadius: 50.0 # meters, within n meters scan-to-map optimization (when loop closure disabled)
  45. # Loop closure
  46. loopClosureEnableFlag: true # use loopclousre or not
  47. loopClosureFrequency: 4.0 # Hz, regulate loop closure constraint add frequency
  48. surroundingKeyframeSize: 50 # submap size (when loop closure enabled)
  49. historyKeyframeSearchRadius: 1.5 # meters, key frame that is within n meters from current pose will be considerd for loop closure
  50. historyKeyframeSearchTimeDiff: 30.0 # seconds, key frame that is n seconds older will be considered for loop closure
  51. historyKeyframeSearchNum: 20 # number of hostory key frames will be fused into a submap for loop closure
  52. historyKeyframeFitnessScore: 0.3 # icp threshold, the smaller the better alignment
  53. # Visualization
  54. globalMapVisualizationSearchRadius: 1000.0 # meters, global map visualization radius
  55. globalMapVisualizationPoseDensity: 10 # meters, global map visualization keyframe density
  56. globalMapVisualizationLeafSize: 1.0 # meters, global map visualization cloud density
  57. # visual iktree_map
  58. locate_mode: false
  59. locate_map: "/home/zx/Downloads/LOAM2/filterGlobalMap.pcd" #"/home/zx/doc/ros_ws/map/open_road/filterGlobalMap.pcd" #/home/zx/Downloads/LOAM2
  60. visulize_IkdtreeMap: true
  61. # visual iktree_map
  62. recontructKdTree: true
  63. # Export settings
  64. savePCD: true # https://github.com/TixiaoShan/LIO-SAM/issues/3
  65. savePCDDirectory: "/Downloads/avia/" # in your home folder, starts and ends with "/". Warning: the code deletes "LOAM" folder then recreates it. See "mapOptimization" for implementation