Simulation 3D Lidar

Lidar sensor model in 3D simulation environment

  • Library:
  • Automated Driving Toolbox / Simulation 3D

Description

The Simulation 3D Lidar block provides an interface to the lidar sensor in a 3D simulation environment. This environment is rendered using the Unreal Engine® from Epic Games®. The block returns a point cloud with the specified field of view and angular resolution. You can also output the distances from the sensor to object points. In addition, you can output the location and orientation of the sensor in the world coordinate system of the scene.

If you set Sample time to -1, the block uses the sample time specified in the Simulation 3D Scene Configuration block. To use this sensor, ensure that the Simulation 3D Scene Configuration block is in your model.

Note

The Simulation 3D Scene Configuration block must execute before the Simulation 3D Lidar block. That way, the Unreal Engine 3D visualization environment prepares the data before the Simulation 3D Lidar block receives it. To check the block execution order, right-click the blocks and select Properties. On the General tab, confirm these Priority settings:

  • Simulation 3D Scene Configuration0

  • Simulation 3D Lidar1

For more information about execution order, see How 3D Simulation for Automated Driving Works.

Ports

Output

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Point cloud data, returned as an m-by-n-by 3 array of positive, real-valued [x, y, z] points. m and n define the number of points in the point cloud, as shown in this equation:

m×n=VFOVVRES×HFOVHRES

where:

  • VFOV is the vertical field of view of the lidar, in degrees, as specified by the Vertical field of view (deg) parameter.

  • VRES is the vertical angular resolution of the lidar, in degrees, as specified by the Vertical resolution (deg) parameter.

  • HFOV is the horizontal field of view of the lidar, in degrees, as specified by the Horizontal field of view (deg) parameter.

  • HRES is the horizontal angular resolution of the lidar, in degrees, as specified by the Horizontal resolution (deg) parameter.

Each m-by-n entry in the array specifies the x, y, and z coordinates of a detected point in the sensor coordinate system. If the lidar does not detect a point at a given coordinate, then x, y, and z are returned as NaN.

You can create a point cloud from these returned points by using point cloud functions in a MATLAB Function block. For a list of point cloud processing functions, see Lidar Processing. For an example that uses these functions, see Simulate Lidar Sensor Perception Algorithm.

Data Types: single

Distance to object points measured by the lidar sensor, returned as an m-by-n positive real-valued matrix. Each m-by-n value in the matrix corresponds to an [x, y, z] coordinate point returned by the Point cloud output port.

Dependencies

To enable this port, on the Parameters tab, select Distance outport.

Data Types: single

Sensor location along the X-axis, Y-axis, and Z-axis of the scene. The Location values are in the world coordinates of the scene. In this coordinate system, the Z-axis points up from the ground. Units are in meters.

Dependencies

To enable this port, on the Ground Truth tab, select Output location (m) and orientation (rad).

Data Types: double

Roll, pitch, and yaw sensor orientation about the X-axis, Y-axis, and Z-axis of the scene. The Orientation values are in the world coordinates of the scene. These values are positive in the clockwise direction when looking in the positive directions of these axes. Units are in radians.

Dependencies

To enable this port, on the Ground Truth tab, select Output location (m) and orientation (rad).

Data Types: double

Parameters

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Mounting

Unique sensor identifier, specified as a positive integer. In a multisensor system, the sensor identifier distinguishes between sensors. When you add a new sensor block to your model, the Sensor identifier of that block is N + 1. N is the highest Sensor identifier value among existing sensor blocks in the model.

Example: 2

Name of the parent to which the sensor is mounted, specified as Scene Origin or as the name of a vehicle in your model. The vehicle names that you can select correspond to the Name parameters of the Simulation 3D Vehicle with Ground Following blocks in your model. If you select Scene Origin, the block places a sensor at the scene origin.

Example: SimulinkVehicle1

Sensor mounting location.

  • When Parent name is Scene Origin, the block mounts the sensor to the origin of the scene, and Mounting location can be set to Origin only. During simulation, the sensor remains stationary.

  • When Parent name is the name of a vehicle (for example, SimulinkVehicle1) the block mounts the sensor to one of the predefined mounting locations described in the table. During simulation, the sensor travels with the vehicle.

Vehicle Mounting LocationDescriptionOrientation Relative to Vehicle Origin [Roll, Pitch, Yaw] (deg)
Origin

Forward-facing sensor mounted to the vehicle origin, which is on the ground, at the geometric center of the vehicle (see Coordinate Systems for 3D Simulation in Automated Driving Toolbox)

[0, 0, 0]
Front bumper

Forward-facing sensor mounted to the front bumper

[0, 0, 0]
Rear bumper

Backward-facing sensor mounted to the rear bumper

[0, 0, 180]
Right mirror

Downward-facing sensor mounted to the right side-view mirror

[0, –90, 0]
Left mirror

Downward-facing sensor mounted to the left side-view mirror

[0, –90, 0]
Rearview mirror

Forward-facing sensor mounted to the rearview mirror, inside the vehicle

[0, 0, 0]
Hood center

Forward-facing sensor mounted to the center of the hood

[0, 0, 0]
Roof center

Forward-facing sensor mounted to the center of the roof

[0, 0, 0]

The (X, Y, Z) location of the sensor relative to the vehicle depends on the vehicle type. To specify the vehicle type, use the Type parameter of the Simulation 3D Vehicle with Ground Following block to which you are mounting. The tables show the X, Y, and Z locations of sensors in the vehicle coordinate system. In this coordinate system:

  • The X-axis points forward from the vehicle.

  • The Y-axis points to the left of the vehicle, as viewed when facing forward.

  • The Z-axis points up from the ground.

  • Roll, pitch, and yaw are clockwise-positive when looking in the positive direction of the X-axis, Y-axis, and Z-axis, respectively. When looking at a vehicle from the top down, then the yaw angle (that is, the orientation angle) is counterclockwise-positive, because you are looking in the negative direction of the axis.

Muscle Car — Sensor Locations Relative to Vehicle Origin

Mounting LocationX (m)Y (m)Z (m)
Front bumper2.4700.45
Rear bumper–2.4700.45

Right mirror

0.43–1.081.01

Left mirror

0.431.081.01

Rearview mirror

0.3201.20

Hood center

1.2801.14

Roof center

–0.2501.58

Sedan — Sensor Locations Relative to Vehicle Origin

Mounting LocationX (m)Y (m)Z (m)
Front bumper2.4200.51
Rear bumper–2.4200.51

Right mirror

0.59–0.941.09

Left mirror

0.590.941.09

Rearview mirror

0.4301.31

Hood center

1.4601.11

Roof center

–0.4501.69

Sport Utility Vehicle — Sensor Locations Relative to Vehicle Origin

Mounting LocationX (m)Y (m)Z (m)
Front bumper2.4200.51
Rear bumper–2.4200.51

Right mirror

0.60–11.35

Left mirror

0.6011.35

Rearview mirror

0.3901.55

Hood center

1.5801.39

Roof center

–0.5602

Small Pickup Truck — Sensor Locations Relative to Vehicle Origin

Mounting LocationX (m)Y (m)Z (m)
Front bumper3.0700.51
Rear bumper–3.0700.51

Right mirror

1.10–1.131.52

Left mirror

1.101.131.52

Rearview mirror

0.8501.77

Hood center

2.2201.59

Roof center

002.27

Hatchback — Sensor Locations Relative to Vehicle Origin

Mounting LocationX (m)Y (m)Z (m)
Front bumper1.9300.51
Rear bumper–1.9300.51

Right mirror

0.43–0.841.01

Left mirror

0.430.841.01

Rearview mirror

0.3201.27

Hood center

1.4401.01

Roof center

001.57

To determine the location of the sensor in world coordinates, open the sensor block. Then, on the Ground Truth tab, select Output location (m) and orientation (rad) and inspect the data from the Location output port.

Select this parameter to specify an offset from the mounting location by using the Relative translation [X, Y, Z] (m) and Relative rotation [Roll, Pitch, Yaw] (deg) parameters.

Translation offset relative to the mounting location of the sensor, specified as a real-valued 1-by-3 vector of the form [X, Y, Z]. Units are in meters.

If you mount the sensor to a vehicle by setting Parent name to the name of that vehicle, then X, Y, and Z are in the vehicle coordinate system, where:

  • The X-axis points forward from the vehicle.

  • The Y-axis points to the left of the vehicle, as viewed when facing forward .

  • The Z-axis points up.

The origin is the mounting location specified in the Mounting location parameter. This origin is different from the vehicle origin, which is the geometric center of the vehicle.

If you mount the sensor to the scene origin by setting Parent name to Scene Origin, then X, Y, and Z are in the world coordinates of the scene.

For more details about the vehicle and world coordinate systems, see Coordinate Systems for 3D Simulation in Automated Driving Toolbox.

Example: [0,0,0.01]

Dependencies

To enable this parameter, select Specify offset.

Rotational offset relative to the mounting location of the sensor, specified as a real-valued 1-by-3 vector of the form [Roll, Pitch, Yaw] . Roll, pitch, and yaw are the angles of rotation about the X-, Y-, and Z-axes, respectively. Units are in degrees.

If you mount the sensor to a vehicle by setting Parent name to the name of that vehicle, then X, Y, and Z are in the vehicle coordinate system, where:

  • The X-axis points forward from the vehicle.

  • The Y-axis points to the left of the vehicle, as viewed when facing forward .

  • The Z-axis points up.

  • Roll, pitch, and yaw are clockwise-positive when looking in the forward direction of the X-axis, Y-axis, and Z-axis, respectively. If you view a scene from a 2D top-down perspective, then the yaw angle (also called the orientation angle) is counterclockwise-positive, because you are viewing the scene in the negative direction of the Z-axis.

The origin is the mounting location specified in the Mounting location parameter. This origin is different from the vehicle origin, which is the geometric center of the vehicle.

If you mount the sensor to the scene origin by setting Parent name to Scene Origin, then X, Y, and Z are in the world coordinates of the scene.

For more details about the vehicle and world coordinate systems, see Coordinate Systems for 3D Simulation in Automated Driving Toolbox.

Example: [0,0,10]

Dependencies

To enable this parameter, select Specify offset.

Sample time of the block in seconds, specified as a positive scalar. The 3D simulation environment frame rate is the inverse of the sample time.

If you set the sample time to -1, the block inherits its sample time from the Simulation 3D Scene Configuration block.

Parameters

Maximum distance measured by the lidar sensor, specified as a positive scalar. Points outside this range are ignored. Units are in meters.

Resolution of the lidar sensor range, in meters, specified as a positive real scalar. The range resolution is also known as the quantization factor. The minimal value of this factor is Drange / 224, where Drange is the maximum distance measured by the lidar sensor, as specified in the Detection range (m) parameter.

Vertical field of view of the lidar sensor, specified as a positive scalar. Units are in degrees.

Vertical angular resolution of the lidar sensor, specified as a positive scalar. Units are in degrees.

Horizontal field of view of the lidar sensor, specified as a positive scalar. Units are in degrees.

Horizontal angular (azimuth) resolution of the lidar sensor, specified as a positive scalar. Units are in degrees.

Select this parameter to output the distance to measured object points at the Distance port.

Ground Truth

Select this parameter to output the location and orientation of the sensor at the Location and Orientation ports, respectively.

Tips

  • To visualize the point clouds that are output by the Point cloud port, use a pcplayer object in a MATLAB Function block. For an example of this visualization setup, see Simulate Lidar Sensor Perception Algorithm.

  • Because the Unreal Engine can take a long time to start up between simulations, consider logging the signals that the sensors output. You can then use this data to develop perception algorithms in MATLAB®. See Configure a Signal for Logging (Simulink).

Introduced in R2019b