Generate lidar point cloud data for a scene
Since R2023a
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Libraries:
Lidar Toolbox
Description
The Lidar Sensor block generates point cloud data from the measurements recorded by a lidar sensor mounted on an ego vehicle. The generated data is in the ego vehicle coordinate system.
To generate point cloud data for a scene, you can configure the sensor and actor poses by using this block. The block also outputs the intensity and segmentation values for the generated points.
Additionally, you can use this block to
configure the lidar sensor parameters such as range, azimuth angles, and elevation angles.
add random Gaussian noise to the points in the point cloud.
simulate weather conditions such as fog and rain.
You can use the drivingScenario (Automated Driving Toolbox) object to create a scenario containing actors and trajectories, import this data into Simulink® by using the Scenario Reader (Automated Driving Toolbox) block and then generate the point cloud data for the scenario by using the Lidar Sensor block.
Ports
Input
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ActorPoses — Actor poses
Simulink bus containing MATLAB® structure
Actor poses, specified as a Simulink bus containing MATLAB structure. The structure must contain these two fields.
Target poses of the actors in the scene, specified as an L- element array of structures. Each structure corresponds to an actor. L is the number of actors used.
You can generate this structure programmatically using the actorPoses (Automated Driving Toolbox) function. You can also create these structures manually. Each structure must contain these fields.
Field Description Value ActorIDUnique identifier for the actor. Positive scalar PositionPosition of the actor with respect to the ego vehicle coordinate system, in meters. Three-element vector of the form [ x y z]VelocityVelocity (V) of the actor, in meters per second, along the x-, y-, and z- directions. Three-element vector of the form [
Vx Vy Vz]RollRoll angle of the actor in degrees. Numeric scalar
PitchPitch angle of the actor in degrees. Numeric scalar
YawYaw angle of the actor in degrees. Numeric scalar
AngularVelocityAngular velocity (ω) of the actor, in degrees per second, along the x-, y-, and z- directions. Three-element vector of the form [
ωx ωy ωz]Simulation time for generating new point clouds, specified as a positive scalar.
You can output the scene actors poses from a Scenario Reader (Automated Driving Toolbox) block.
Output
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IsValid — Valid simulation time
0 | 1
Valid simulation time, returned as a logical 0 (false) or 1 (true). This value is 0 for the updates requested at times between the update interval specified by the Required interval between sensor updates (s) parameter.
Data Types: Boolean
Location — Location values of points
M-by-N-by-3 matrix
Location values of points in the point cloud, returned as an M-by-N-by-3 matrix. M, N are the number of rows and columns in the organized point cloud, respectively.
Intensity — Intensity values of points
M-by-N matrix
Intensity values of points in the point cloud, returned as an M-by-N matrix. M, N are the number of rows and columns in the organized point cloud, respectively.
Clusters — Classification data of actors
M-by-N-by-2 matrix
Classification data of actors in the scene, returned as an M-by-N-by-2 matrix. The first column contains the ActorIDs and the second column contains the ClassIDs of the target actors.M, N are the number of rows and columns in the organized point cloud, respectively.
Parameters
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Parameters
Sensor Identification
Unique identifier of sensor — Unique sensor identifier
1 (default) | positive integer
Unique identifier for the sensor, specified as a positive integer. In a multisensor system, this index distinguishes different sensors from one another.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Required interval between sensor updates (s) — Required time interval between sensor updates
0.1 (default) | positive scalar
Time interval between two consecutive sensor updates, specified as a positive scalar. The block generates new detections at the interval specified by this parameter. The value must be an integer multiple of the simulation time. Updates requested from the sensor in between the update intervals contain no detections. Units are in seconds.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Sensor Mounting
Position [X Y Height] (m) — Sensor center position
[1.5 0 1.6] (default) | three-element vector of form [X Y Height]
Sensor center position, specified as a three-element vector of the form [X Y Height]. The values of X and Y represent the location of the sensor center with respect to the X- and Y-axes of the ego vehicle coordinate system. Height is the height of the sensor above the ground. The default value defines a lidar sensor mounted on the front edge of the roof of a sedan. Units are in meters.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Orientation [Roll Pitch Yaw] (deg) — Sensor orientation
[0 0 0] (default) | three-element vector
Sensor orientation, specified as a three-element vector of the form, [Roll Pitch Yaw]. These values are with respect to the ego vehicle coordinate system. Units are in degrees.
Roll — The roll angle is the angle of rotation around the front-to-back axis, which is the x-axis of the ego vehicle coordinate system. A positive roll angle corresponds to a clockwise rotation when looking in the positive direction of the x-axis.
Pitch — The pitch angle is the angle of rotation around the side-to-side axis, which is the y-axis of the ego vehicle coordinate system. A positive roll angle corresponds to a clockwise rotation when looking in the positive direction of the y-axis.
Yaw — The yaw angle is the angle of rotation around the vertical axis,which is the z-axis of the ego vehicle coordinate system. A positive roll angle corresponds to a clockwise rotation when looking in the positive direction of the z-axis. This rotation appears counter-clockwise when viewing the vehicle from above.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Actor Profiles
MATLAB or Model workspace Actor profiles variable name — Variable name for actor profiles
actor_profiles (default) | valid variable name
Variable name for actor profiles, specified as the name of a MATLAB or model workspace variable containing actor profiles.
Actor profiles are the physical characteristics of the actors in the scene, specified as a structure or as an L-element array of structures. L is the number of actors in the scene.
If the actor profiles variable has a single structure, then all actors specified at the ActorPoses input port use the same profile.
To generate an array of actor profile structures for your driving scenario drivingScenario (Automated Driving Toolbox), use the actorProfiles (Automated Driving Toolbox) function. You can also create these structures manually. This table shows the valid structure fields.
| Field | Description | Value | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ActorID | Unique identifier for the actor. In a scene with multiple actors, this value distinguishes different actors from one another. | Positive integer | ||||||||||||||
ClassID | User-defined classification ID for the actor.
| Positive scalar | ||||||||||||||
Length | Length of the actor in meters. | Positive scalar | ||||||||||||||
Width | Width of the actor in meters. | Positive scalar | ||||||||||||||
Height | Height of the actor in meters. | Positive scalar | ||||||||||||||
OriginOffset | Offset of the rotational center of the actor from its geometric center. The rotational center, or origin, is located at the bottom center of the actor. For vehicles, the rotational center is the point on the ground beneath the center of the rear axle. | A three-element vector of the form | ||||||||||||||
MeshVertices | Vertices of the actor in mesh representation. | N-by-3 numeric matrix, where each row defines a vertex in 3-D space. | ||||||||||||||
MeshFaces | Face of the actor in mesh representation. | M-by-3 integer matrix, where each row represents a triangle defined by vertex IDs, which are the row numbers of MeshVertices. | ||||||||||||||
MeshTargetReflectances | Material reflectance for each triangular face of the actor. | M-by-1 numeric vector, where M is the number of triangle faces of the actor. Each value must be in the range [0, 1]. |
For more information about these structure fields, see the actor (Automated Driving Toolbox) and vehicle (Automated Driving Toolbox) functions.
ActorID of the host vehicle — Actor ID of ego vehicle
1 (default) | positive integer
ActorID value of the ego vehicle, specified as a positive integer. ActorID is the unique identifier for an actor. This parameter must be a valid ActorID specified at the ActorPoses input port.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Sensor FOV
Settings
Maximum detection range of sensor (m) — Maximum detection range
120 (default) | positive scalar
Maximum detection range of the sensor specified as a positive scalar. The sensor cannot scan for the points beyond this range. Units are in meters.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Azimuth limits (deg) — Azimuth limits of lidar sensor
[-180 180] (default) | two-element vector
Azimuth limits of the lidar sensor, specified as a two-element vector of the form [min max]. The values must be in the range [-180, 180], max must be greater than min. Units are in degrees.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Azimuth resolution (deg) — Azimuthal resolution of lidar sensor
0.16 (default) | positive scalar
Azimuthal resolution of the lidar sensor, specified as a positive scalar. Units are in degrees.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Use custom elevation angles — Use custom elevation angles
off (default) | on
Select this parameter to use custom elevation angles.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Custom elevation angles (deg) — Elevation angles of lidar sensor
N-element real-valued vector
Custom elevation angles of the lidar sensor, specified as an N-element real-valued vector. N is the number of elevation channels. The elements of the vector must be in the increasing order. Units are in degrees.
Dependencies
To enable this parameter, select the Use custom elevation angles parameter.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Elevation limits (deg) — Elevation limits of lidar sensor
[-20 20] (default) | two element vector of form [min, max]
Elevation limits of the lidar sensor, specified as a two-element vector of the form [min max]. The values must be in the range [-180, 180], max must be greater than min. Units are in degrees.
Note
The block disables this parameter, when you select the Use custom elevation angles parameter.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Elevation resolution (deg) — Elevation resolution of lidar sensor
1.25 (default) | positive scalar
Elevation resolution of the lidar sensor, specified as a positive scalar in degrees.
Note
The block disables this parameter, when you select the Use custom elevation angles parameter.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Advance Settings
Noise Simulation
Add noise to measurements — Add noise to measurements
on (default) | off
When you select this parameter, the block adds random Gaussian noise to each point in the point cloud using the Range accuracy (m) parameter as one standard deviation. Otherwise, the data has no noise.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Range accuracy (m) — Accuracy of sensor range measurement
0.002 (default) | positive scalar
Accuracy of the sensor range measurement, specified as a positive scalar. Units are in meters.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Weather Simulation
Fog visibility in meters — Visible distance in fog
1000 (default) | positive scalar
Visible distance in fog, specified as a positive scalar, in meters. The value of this parameter must not be greater than 1000. A higher value indicates a better visibility and a lower fog impact. The default value of 1000 indicates clear visibility, or no fog.
Note
When you specify both Fog visibility in meters and Rainrate in mm/hour parameters, the block simulates only the foggy weather.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Rainrate in mm/hour — Rate of rainfall
0 (default) | positive scalar
Rate of rainfall, specified as a positive scalar in millimeter per hour. The value of this parameter must not be greater than 200. Increasing this value increases the impact of rain on the generated point cloud. The default value is 0, indicating no rainfall.
Note
When you specify both Fog visibility in meters and Rainrate in mm/hour parameters, the block simulates only the foggy weather.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
Output Port Settings
Output intensity port — Output intensity values of points
on (default) | off
Select this parameter to enable the Intensity output port.
Output clusters port — Output segmentation values of points
on (default) | off
Select this parameter to enable the Clusters output port.
Version History
Introduced in R2023a
See Also
Apps
- Driving Scenario Designer (Automated Driving Toolbox) | Lidar Viewer | Lidar Labeler
Blocks
- Scenario Reader (Automated Driving Toolbox) | Point Cloud Viewer
Functions
- actorProfiles (Automated Driving Toolbox) | actorPoses (Automated Driving Toolbox)
Objects
- lidarSensor | drivingScenario (Automated Driving Toolbox)
Topics
- Coordinate Systems in Lidar Toolbox
- Generate Lidar Point Cloud Data for Driving Scenario with Multiple Actors
MATLAB-Befehl
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FAQs
How do I create a point cloud data LiDAR? ›
Different LiDAR units have different methods, but generally they sweep in a circle like a RADAR dish, while simultaneously moving the laser up and down. Once the individual readings are processed and organised, the LiDAR data becomes point cloud data.
How do I get data from LiDAR? ›- 3DEP LidarExplorer – Point cloud data and lidar-derived DEMs.
- The National Map Download Client.
- The National Map Services.
Third, in the right menu panel, open the “Lidar within AOI” drop-down and click on the “LiDAR Point Cloud (LPC)” folder. Finally, select download the individual LiDAR (LAS) files that you need from the folder. The map viewer will show where each tile is relative to your area of interest.
What are three ways that LiDAR data can be collected? ›ArcGIS provides several complimentary options for accessing lidar. There are three primary data access mechanisms: the LAS dataset, the terrain dataset, and the mosaic dataset. Knowing about these data types will let you determine which type to use.