# RoboSense (E1R / RSE1) LiDAR configuration for the polymath lidar test bench.

lidar:
  # ── Identity ──────────────────────────────────────────────────────────────
  frame:               rslidar      # TF frame / URDF link name
  folder:              E1R          # Results folder and Notion identifier
  point_cloud_topic:   /rslidar_points

  # ── Mount pose (lidar_joint in lidar_bench.urdf) ──────────────────────────
  joint_xyz_m:         [0.0, 0.0, 0.05]    # offset from motor_axis (m)
  joint_rpy_rad:       [0.0, 0.0, 0.0]     # no rotation

  # ── Bench geometry ────────────────────────────────────────────────────────
  map_to_motor_height_m:   0.9406   # vertical distance, ground (map) -> motor_axis (m)
  motor_to_lidar_height_m: 0.0889   # vertical distance, motor_axis -> lidar (m)

  # ── Driver ────────────────────────────────────────────────────────────────
  ros2_driver:         rslidar_sdk
  driver_command:      'ros2 run rslidar_sdk rslidar_sdk_node'
  driver_config_file:  '/workspaces/polymath_workspace/src/rslidar_sdk/config/config.yaml'
  lidar_gui:           ''                                    # empty disables GUI prompt

  # eventually remove the bottom two angles completely


  # ── Sweep ─────────────────────────────────────────────────────────────────
  angles:              [10.0, -7.0]                         # servo angles to sweep (deg)
  parameter_names:     [min_distance, max_distance, dense_points, start_angle, end_angle]



  # -- Include parameters specific to lidar
  horizontal_fov_deg: 120.0
  vertical_fov_deg: 90.0
  horizontal_resolution_deg: 0.625
  vertical_resolution_deg: 0.625
  cost: 999.0

  # TODO: 1. Use horizontal fov and vertical fov to compute panning and tilting angles
  #       2. Use the resolutions for both in degrees + geometry to compute distance
  #       3. maybe attach a link to an image here somewhere
  #       4. sen the cost, vertical and horizontal fov's, and the image somehow to the front lines


  # Minimum point distance — clips returns closer than this.
  min_distance:
    type:    double
    default: 0.2
    values:  [0.2, 1.0, 5.0]
    path:    lidar.0.driver.min_distance
    description: Minimum range threshold in meters. Returns closer than this value are filtered out to prevent self-occlusion from the vehicle body or sensor housing.

  # Maximum point distance — clips returns farther than this.
  max_distance:
    type:    double
    default: 200.0
    values:  [100.0, 200.0, 500.0]
    path:    lidar.0.driver.max_distance
    description: Maximum range threshold in meters. Filters out distant, low-confidence returns to optimize data processing and limit the maximum depth of the point cloud.

  # If true, discard NaN points; if false, keep them as placeholders.
  dense_points:
    type:    bool
    default: false
    values:  [true, false]
    path:    lidar.0.driver.dense_points
    description: When true, filters out invalid or unreturned (NaN) points to produce a smaller, compact point cloud. When false, preserves the fixed array structure by keeping NaNs as placeholders.

  # FOV trimming in degrees (RoboSense uses [start, end] over 0..360).
  start_angle:
    type:    int
    default: 0
    values:  [0, 30, 60]
    path:    lidar.0.driver.start_angle
    description: Starting azimuth angle in degrees for the horizontal Field of View (FOV) clipping window. Defines the beginning of the active scanning sector.

  end_angle:
    type:    int
    default: 360
    values:  [360, 330, 300]
    path:    lidar.0.driver.end_angle
    description: Ending azimuth angle in degrees for the horizontal Field of View (FOV) clipping window. Defines the termination point of the active scanning sector.