How to Use Lidar in Colosseum#

Colosseum supports Lidar for multirotors and cars.

The enablement of lidar and the other lidar settings can be configured via ColosseumSettings json. Please see general sensors for information on configruation of general/shared sensor settings.

Enabling lidar on a vehicle#

  • By default, lidars are not enabled. To enable lidar, set the SensorType and Enabled attributes in settings json.
    "Lidar1": {
         "SensorType": 6,
         "Enabled" : true,
    }
  • Multiple lidars can be enabled on a vehicle.

Lidar configuration#

The following parameters can be configured right now via settings json.

Parameter Description
NumberOfChannels Number of channels/lasers of the lidar
Range Range, in meters
PointsPerSecond Number of points captured per second
RotationsPerSecond Rotations per second
HorizontalFOVStart Horizontal FOV start for the lidar, in degrees
HorizontalFOVEnd Horizontal FOV end for the lidar, in degrees
VerticalFOVUpper Vertical FOV upper limit for the lidar, in degrees
VerticalFOVLower Vertical FOV lower limit for the lidar, in degrees
X Y Z Position of the lidar relative to the vehicle (in NED, in meters)
Roll Pitch Yaw Orientation of the lidar relative to the vehicle (in degrees, yaw-pitch-roll order to front vector +X)
DataFrame Frame for the points in output ("VehicleInertialFrame" or "SensorLocalFrame")
ExternalController Whether data is to be sent to external controller such as ArduPilot or PX4 if being used (default true) (PX4 doesn't send Lidar data currently)

e.g.

{
    "SeeDocsAt": "https://CodexLabsLLC.github.io/Colosseum/settings/",
    "SettingsVersion": 1.2,

    "SimMode": "Multirotor",

     "Vehicles": {
        "Drone1": {
            "VehicleType": "simpleflight",
            "AutoCreate": true,
            "Sensors": {
                "LidarSensor1": {
                    "SensorType": 6,
                    "Enabled" : true,
                    "NumberOfChannels": 16,
                    "RotationsPerSecond": 10,
                    "PointsPerSecond": 100000,
                    "X": 0, "Y": 0, "Z": -1,
                    "Roll": 0, "Pitch": 0, "Yaw" : 0,
                    "VerticalFOVUpper": -15,
                    "VerticalFOVLower": -25,
                    "HorizontalFOVStart": -20,
                    "HorizontalFOVEnd": 20,
                    "DrawDebugPoints": true,
                    "DataFrame": "SensorLocalFrame"
                },
                "LidarSensor2": {
                   "SensorType": 6,
                    "Enabled" : true,
                    "NumberOfChannels": 4,
                    "RotationsPerSecond": 10,
                    "PointsPerSecond": 10000,
                    "X": 0, "Y": 0, "Z": -1,
                    "Roll": 0, "Pitch": 0, "Yaw" : 0,
                    "VerticalFOVUpper": -15,
                    "VerticalFOVLower": -25,
                    "DrawDebugPoints": true,
                    "DataFrame": "SensorLocalFrame"
                }
            }
        }
    }
}

Server side visualization for debugging#

By default, the lidar points are not drawn on the viewport. To enable the drawing of hit laser points on the viewport, please enable setting DrawDebugPoints via settings json.

    "Lidar1": {
         ...
         "DrawDebugPoints": true
    },

Note: Enabling DrawDebugPoints can cause excessive memory usage and crash in releases v1.3.1, v1.3.0. This has been fixed in the main branch and should work in later releases

Client API#

Use getLidarData() API to retrieve the Lidar data.

  • The API returns a Point-Cloud as a flat array of floats along with the timestamp of the capture and lidar pose.
  • Point-Cloud:
    • The floats represent [x,y,z] coordinate for each point hit within the range in the last scan.
    • The frame for the points in the output is configurable using "DataFrame" attribute -
      • "" or VehicleInertialFrame -- default; returned points are in vehicle inertial frame (in NED, in meters)
      • SensorLocalFrame -- returned points are in lidar local frame (in NED, in meters)
  • Lidar Pose:
    • Lidar pose in the vehicle inertial frame (in NED, in meters)
    • Can be used to transform points to other frames.
  • Segmentation: The segmentation of each lidar point's collided object

Python Examples#

Coming soon#

  • Visualization of lidar data on client side.