Parameters

There are three parameter files:

  1. Robot Setup Configurations

  2. Plugin configurations

  3. Core Parameters

  4. Sensor parameter

Robot Setup Configurations

Such as Publishers and subscribers

#### Plugins ########
plugin_config_file: '$(rospack find elevation_mapping_cupy)/config/core/plugin_config.yaml'

#### Channel Fusions ########
pointcloud_channel_fusions:
  rgb: 'color'                # 'color' fusion is used for the 'rgb' channel
  default: 'average'          # 'average' fusion is used for channels not listed here

image_channel_fusions:
  rgb: 'color'                # 'color' fusion is used for the 'rgb' channel
  default: 'exponential'      # 'exponential' fusion is used for channels not listed here
  feat_.*: 'exponential'      # 'exponential' fusion is also used for any channel starting with 'feat_' Regular expressions can be used for channel names

#### Subscribers ########
#  pointcloud_sensor_name:
#    topic_name: '/sensor/pointcloud_semantic'
#    data_type:  pointcloud  # pointcloud or image
#
#  image_sensor_name:
#    topic_name: '/camera/image_semantic'
#    data_type:  image  # pointcloud or image
#    camera_info_topic_name: '/camera/depth/camera_info'
#    channel_info_topic_name: '/camera/channel_info'


subscribers:
  front_cam:
    topic_name: '/camera/depth/points'
    data_type: pointcloud
  color_cam: # for color camera
    topic_name: '/camera/rgb/image_raw'
    camera_info_topic_name: '/camera/depth/camera_info'
    data_type: image
  semantic_cam: # for semantic images
    topic_name: '/front_cam/semantic_image'
    camera_info_topic_name: '/front_cam/camera/depth/camera_info_resized'
    channel_info_topic_name: '/front_cam/channel_info'
    data_type: image

#### Publishers ########
# topic_name:
#   layers:               # Choose from 'elevation', 'variance', 'traversability', 'time', 'normal_x', 'normal_y', 'normal_z', 'color', plugin_layer_names
#   basic_layers:         # basic_layers for valid cell computation (e.g. Rviz): Choose a subset of `layers`.
#   fps:                  # Publish rate. Use smaller value than `map_acquire_fps`.

publishers:
  elevation_map_raw:
    layers: ['elevation', 'traversability', 'variance','rgb']
    basic_layers: ['elevation']
    fps: 5.0
  elevation_map_recordable:
   layers: ['elevation', 'traversability']
   basic_layers: ['elevation', 'traversability']
   fps: 2.0
  elevation_map_filter:
    layers: ['min_filter', 'smooth', 'inpaint', 'elevation']
    basic_layers: ['min_filter']
    fps: 3.0

Plugin configurations

More informations on the plugins can be found in Plugins.

# Settings of the plugins. (The plugins should be stored in script/plugins)

# min_filter fills in minimum value around the invalid cell.
min_filter:
  enable: True                                # weather to load this plugin
  fill_nan: False                             # Fill nans to invalid cells of elevation layer.
  is_height_layer: True                       # If this is a height layer (such as elevation) or not (such as traversability)
  layer_name: "min_filter"                    # The layer name.
  extra_params:                               # This params are passed to the plugin class on initialization.
    dilation_size: 1                         # The patch size to apply
    iteration_n: 30                           # The number of iterations
# Apply smoothing.
smooth_filter:
  enable: True
  fill_nan: False
  is_height_layer: True
  layer_name: "smooth"
  extra_params:
    input_layer_name: "min_filter"
# Apply inpainting using opencv
inpainting:
  enable: True
  fill_nan: False
  is_height_layer: True
  layer_name: "inpaint"
  extra_params:
    method: "telea"                           # telea or ns
# Apply smoothing for inpainted layer
erosion:
  enable: True
  fill_nan: False
  is_height_layer: False
  layer_name: "erosion"
  extra_params:
    input_layer_name: "traversability"
    dilation_size: 3
    iteration_n: 20
    reverse: True

Core Parameters

#### Basic parameters ########
resolution: 0.04                                # resolution in m.
map_length: 8.0                                 # map's size in m.
sensor_noise_factor: 0.05                       # point's noise is sensor_noise_factor*z^2 (z is distance from sensor).
mahalanobis_thresh: 2.0                         # points outside this distance is outlier.
outlier_variance: 0.01                          # if point is outlier, add this value to the cell.
drift_compensation_variance_inler: 0.05         # cells under this value is used for drift compensation.
max_drift: 0.1                                  # drift compensation happens only the drift is smaller than this value (for safety)
drift_compensation_alpha: 0.1                   # drift compensation alpha for smoother update of drift compensation
time_variance: 0.0001                           # add this value when update_variance is called.
max_variance: 100.0                             # maximum variance for each cell.
initial_variance: 1000.0                         # initial variance for each cell.
traversability_inlier: 0.9                      # cells with higher traversability are used for drift compensation.
dilation_size: 3                                # dilation filter size before traversability filter.
wall_num_thresh: 20                             # if there are more points than this value, only higher points than the current height are used to make the wall more sharp.
min_height_drift_cnt: 100                       # drift compensation only happens if the valid cells are more than this number.
position_noise_thresh: 0.01                     # if the position change is bigger than this value, the drift compensation happens.
orientation_noise_thresh: 0.01                  # if the orientation change is bigger than this value, the drift compensation happens.
position_lowpass_alpha: 0.2                     # lowpass filter alpha used for detecting movements.
orientation_lowpass_alpha: 0.2                  # lowpass filter alpha used for detecting movements.
min_valid_distance: 0.5                         # points with shorter distance will be filtered out.
max_height_range: 1.0                           # points higher than this value from sensor will be filtered out to disable ceiling.
ramped_height_range_a: 0.3                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
ramped_height_range_b: 1.0                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
ramped_height_range_c: 0.2                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
update_variance_fps: 5.0                        # fps for updating variance.
update_pose_fps: 10.0                           # fps for updating pose and shift the center of map.
time_interval: 0.1                              # Time layer is updated with this interval.
map_acquire_fps: 5.0                            # Raw map is fetched from GPU memory in this fps.
publish_statistics_fps: 1.0                     # Publish statistics topic in this fps.

max_ray_length: 10.0                            # maximum length for ray tracing.
cleanup_step: 0.1                               # subtitute this value from validity layer at visibiltiy cleanup.
cleanup_cos_thresh: 0.1                         # subtitute this value from validity layer at visibiltiy cleanup.

safe_thresh: 0.7                                # if traversability is smaller, it is counted as unsafe cell.
safe_min_thresh: 0.4                            # polygon is unsafe if there exists lower traversability than this.
max_unsafe_n: 10                                # if the number of cells under safe_thresh exceeds this value, polygon is unsafe.

overlap_clear_range_xy: 4.0                     # xy range [m] for clearing overlapped area. this defines the valid area for overlap clearance. (used for multi floor setting)
overlap_clear_range_z: 2.0                      # z range [m] for clearing overlapped area. cells outside this range will be cleared. (used for multi floor setting)

map_frame: 'odom'                               # The map frame where the odometry source uses.
base_frame: 'base_footprint'                              # The robot's base frame. This frame will be a center of the map.
corrected_map_frame: 'odom'

#### Feature toggles ########
enable_edge_sharpen: true
enable_visibility_cleanup: true
enable_drift_compensation: true
enable_overlap_clearance: true
enable_pointcloud_publishing: false
enable_drift_corrected_TF_publishing: false
enable_normal_color: false                      # If true, the map contains 'color' layer corresponding to normal. Add 'color' layer to the publishers setting if you want to visualize.

#### Traversability filter ########
use_chainer: false                              # Use chainer as a backend of traversability filter or pytorch. If false, it uses pytorch. pytorch requires ~2GB more GPU memory compared to chainer but runs faster.
weight_file: '$(rospack find elevation_mapping_cupy)/config/core/weights.dat'               # Weight file for traversability filter

#### Upper bound ########
use_only_above_for_upper_bound: false

#### Initializer ########
initialize_method: 'linear'                                         # Choose one from 'nearest', 'linear', 'cubic'
initialize_frame_id: ['base_footprint']   # One tf (like ['footprint'] ) initializes a square around it.
initialize_tf_offset: [0.0, 0.0, 0.0, 0.0]                          # z direction. Should be same number as initialize_frame_id.
dilation_size_initialize: 2                                         # dilation size after the init.
initialize_tf_grid_size: 0.5                                        # This is not used if number of tf is more than 3.
use_initializer_at_start: true                                      # Use initializer when the node starts.

#### Default Plugins ########
plugin_config_file: '$(rospack find elevation_mapping_cupy)/config/core/plugin_config.yaml'

Sensor parameter

More informations on the sensor configurations can be found in Semantics.

front_cam_pointcloud:
  channels: ['rgb', 'chair','sofa',"person" ]
  fusion: ['color','class_average','class_average','class_average']
  topic_name: 'front_camera/semantic_pointcloud'
  semantic_segmentation: True
  publish_segmentation_image: True
  segmentation_model: 'lraspp_mobilenet_v3_large' # detectron_coco_panoptic_fpn_R_101_3x, lraspp_mobilenet_v3_large
  show_label_legend: False
  data_type: pointcloud

  cam_info_topic: "camera/depth/camera_info"
  image_topic: "camera/rgb/image_raw"
  depth_topic: "camera/depth/image_raw"
  cam_frame: "camera_rgb_optical_frame"

front_cam_image:
  channels: ['chair','sofa',"person"]
  fusion_methods: ['exponential','exponential','exponential']
  publish_topic: 'semantic_image'
  publish_image_topic: "semantic_image_debug"
  publish_camera_info_topic: 'semantic_image_info'
  publish_fusion_info_topic: 'semantic_image_fusion_info'
  data_type: image

  semantic_segmentation: True
  feature_extractor: True
  segmentation_model: 'lraspp_mobilenet_v3_large' # detectron_coco_panoptic_fpn_R_101_3x, lraspp_mobilenet_v3_large
  show_label_legend: False
  image_topic: "camera/rgb/image_raw"
  camera_info_topic: "camera/depth/camera_info"
  resize: 0.5