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LiDAR Marker Localizer#

LiDARMarkerLocalizer is a detect-reflector-based localization node .

Inputs / Outputs#

lidar_marker_localizer node#

Input#

Name Type Description
~/input/lanelet2_map autoware_map_msgs::msg::HADMapBin Data of lanelet2
~/input/pointcloud sensor_msgs::msg::PointCloud2 PointType: PointXYZIRC is recommended in Autoware, but PointXYZIRADRT are also supported in this node.1
~/input/ekf_pose geometry_msgs::msg::PoseWithCovarianceStamped EKF Pose

Output#

Name Type Description
~/output/pose_with_covariance geometry_msgs::msg::PoseWithCovarianceStamped Estimated pose
/diagnostics diagnostic_msgs::msg::DiagnosticArray Diagnostics outputs
For debug#
Name Type Description
~/debug/pose_with_covariance geometry_msgs::msg::PoseWithCovarianceStamped Estimated pose
~/debug/marker_detected geometry_msgs::msg::PoseArray Detected marker poses
~/debug/marker_mapped visualization_msgs::msg::MarkerArray Loaded landmarks to visualize in Rviz as thin boards
~/debug/marker_pointcloud sensor_msgs::msg::PointCloud2 PointCloud of the detected marker
~/debug/center_intensity_grid nav_msgs::msg::OccupancyGrid Center intensity grid for debug
~/debug/positive_grid nav_msgs::msg::OccupancyGrid Positive match grid for debug
~/debug/negative_grid nav_msgs::msg::OccupancyGrid Negative match grid for debug
~/debug/matched_grid nav_msgs::msg::OccupancyGrid Matched pattern grid for debug
~/debug/vote_grid nav_msgs::msg::OccupancyGrid Vote grid for marker detection debug

Parameters#

Name Type Description Default Range
enable_read_all_target_ids boolean true N/A
target_ids array List of target marker IDs to be detected. ["0000", "0001", "0002", "0003", "0004", "0005"] N/A
queue_size_for_output_pose float Queue size for output/pose_with_covariance publisher 10 ≥0
marker_name string The name of the markers listed in the HD map. reflector N/A
resolution float Grid size for marker detection algorithm. [m] 0.05 ≥0.0
intensity_pattern array A sequence of high/low intensity to perform pattern matching. 1: high intensity (positive match), 0: not consider, -1: low intensity (negative match) [-1, -1, 0, 1, 1, 1, 1, 1, 0, -1, -1] N/A
match_intensity_difference_threshold float Threshold for determining high/low. 20 ≥0
positive_match_num_threshold float Threshold for the number of required matches with the pattern. 3 ≥0
negative_match_num_threshold float Threshold for the number of required matches with the pattern. 3 ≥0
vote_threshold_for_detect_marker float Threshold for the number of rings matching the pattern needed to detect it as a marker. 20 ≥0
marker_to_vehicle_offset_y float Y-axis offset from the center of the marker to vehicle. [m] 0.0 N/A
marker_height_from_ground float Height from the ground to the center of the marker. [m] 1.075 N/A
lower_ring_id_init float Initial value when searching for the lowest ring ID within the point cloud 128 ≥0
upper_ring_id_init float Initial value when searching for the highest ring ID within the point cloud 0 ≥0
reference_ring_number float Reference ring number when detecting the marker. Set 255 to disable ring filtering 255 N/A
self_pose_timeout_sec float Timeout for self pose. [sec] 1.0 ≥0.0
self_pose_distance_tolerance_m float Tolerance for the distance between two points when performing linear interpolation. [m] 1.0 ≥0.0
limit_distance_from_self_pose_to_nearest_marker float Distance limit for the purpose of determining whether the node should detect a marker. [m] 2.0 ≥0.0
limit_distance_from_self_pose_to_nearest_marker_y float Y-axis distance limit for the purpose of determining whether the node should detect a marker. [m] 1.0 ≥0.0
limit_distance_from_self_pose_to_marker float Distance limit for avoiding miss detection. [m] 2.0 ≥0.0
base_covariance array Output covariance in the base_link coordinate. [0.04, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 7.569e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 7.569e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.00030625] N/A
marker_width float Width of a marker. This param is used for visualizing the detected marker pointcloud[m] 0.8 ≥0.0
enable_save_log boolean false N/A
save_file_directory_path string $(env HOME)/detected_reflector_intensity N/A
save_file_name string detected_reflector_intensity N/A
save_frame_id string velodyne_top N/A
radius_for_extracting_marker_pointcloud float Only points closer than this value to the marker center on the xy plane are extracted as the “marker point cloud”. [m] 0.4 ≥0.0
queue_size_for_debug_pub_msg float Queue size for debug publishers 10 ≥0.0

How to launch#

When launching Autoware, set lidar-marker for pose_source.

ros2 launch autoware_launch ... \
    pose_source:=lidar-marker \
    ...

Design#

Flowchart#

uml diagram

Detection Algorithm#

detection_algorithm

  1. Split the LiDAR point cloud into rings along the x-axis of the base_link coordinate system at intervals of the resolution size.
  2. Find the portion of intensity that matches the intensity_pattern.
  3. Perform steps 1 and 2 for each ring, accumulate the matching indices, and detect portions where the count exceeds the vote_threshold_for_detect_marker as markers.

Sample Dataset#

This dataset was acquired in National Institute for Land and Infrastructure Management, Full-scale tunnel experiment facility. The reflectors were installed by Taisei Corporation.

Collaborators#

  1. Assumed ring of PointXYZIRADRT as channel of PointXYZIRC. ↩