Simulation 3D Lidar

Lidar sensor model in 3D simulation environment

• 

×

Libraries:
Offroad Autonomy Library / Simulation 3D
Automated Driving Toolbox / Simulation 3D
Robotics System Toolbox / Simulation 3D
Simulink 3D Animation / Simulation 3D / Sensors
UAV Toolbox / Simulation 3D

Description

Note

Simulating models with the Simulation 3D Lidar block requires Simulink^® 3D Animation™.

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 and the reflectivity of surface materials. 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.

Tip

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 Configuration — 0

• Simulation 3D Lidar — 1

For more information about execution order, see How Unreal Engine Simulation for Automated Driving Works.

Examples

Design Lidar SLAM Algorithm Using Unreal Engine Simulation Environment

Develop a simultaneous localization and mapping algorithm using synthetic lidar sensor data recorded from the Unreal Engine simulation environment.

• Open Live Script

Visualize Sensor Data from Unreal Engine Simulation Environment

Visualize sensor coverage areas and detections obtained from high-fidelity radar and lidar sensors in the Unreal Engine simulation environment.

• Open Live Script

Ports

Output

Point cloud — Point cloud data

m-by-n-by-3 array of positive real-valued [x, y, z] points

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:

$$m\times n=\frac{V_{FOV}}{V_{RES}}\times \frac{H_{FOV}}{H_{RES}}$$

where:

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

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

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

• H_RES 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 Design Lidar SLAM Algorithm Using Unreal Engine Simulation Environment.

Data Types: single

Distance — Distance to object points

m-by-n positive real-valued matrix

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

Reflectivity — Reflectivity of surface materials

m-by-n matrix of intensity values in range [0, 1]

Reflectivity of surface materials, returned as an m-by-n matrix of intensity values in the range [0, 1], where m is the number of rows in the point cloud and n is the number of columns. Each point in the Reflectivity output corresponds to a point in the Point cloud output. The block returns points that are not part of a surface material as NaN.

To calculate reflectivity, the lidar sensor uses the Phong reflection model. This model describes surface reflectivity as a combination of diffuse reflections (scattered reflections, such as from rough surfaces) and specular reflections (mirror-like reflections, such as from smooth surfaces). For more details on this model, see the Phong reflection model page on Wikipedia.

Dependencies

To enable this port, select the Reflectivity outport parameter.

Data Types: single

Labels — Label identifiers

m-by-n array of label identifiers

Label identifier for each point in the point cloud, output as an m-by-n array. Each m-by-n value in the matrix corresponds to an [x, y, z] coordinate point returned by the Point cloud output port.

The table shows the object IDs used in the default scenes that are selectable from the Simulation 3D Scene Configuration block. If you are using a custom scene, in the Unreal^® Editor, you can assign new object types to unused IDs. For more details, see Apply Labels to Unreal Scene Elements for Semantic Segmentation and Object Detection. If a scene contains an object that does not have an assigned ID, that object is assigned an ID of 0. The detection of lane markings is not supported.

ID	Type
0	None/default
1	Building
2	Not used
3	Other
4	Pedestrians
5	Pole
6	Lane Markings
7	Road
8	Sidewalk
9	Vegetation
10	Vehicle
11	Not used
12	Generic traffic sign
13	Stop sign
14	Yield sign
15	Speed limit sign
16	Weight limit sign
17-18	Not used
19	Left and right arrow warning sign
20	Left chevron warning sign
21	Right chevron warning sign
22	Not used
23	Right one-way sign
24	Not used
25	School bus only sign
26-38	Not used
39	Crosswalk sign
40	Not used
41	Traffic signal
42	Curve right warning sign
43	Curve left warning sign
44	Up right arrow warning sign
45-47	Not used
48	Railroad crossing sign
49	Street sign
50	Roundabout warning sign
51	Fire hydrant
52	Exit sign
53	Bike lane sign
54-56	Not used
57	Sky
58	Curb
59	Flyover ramp
60	Road guard rail
61	Bicyclist
62-66	Not used
67	Deer
68-70	Not used
71	Barricade
72	Motorcycle
73-255	Not used

Dependencies

To enable this port, on the Ground Truth tab, select Output semantic segmentation.

Data Types: uint8

Translation — Sensor location

real-valued 1-by-3 vector

Sensor location along the X-axis, Y-axis, and Z-axis of the scene. The Translation 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

Rotation — Sensor orientation

real-valued 1-by-3 vector

Roll, pitch, and yaw sensor orientation about the X-axis, Y-axis, and Z-axis of the scene. The Rotation 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

Mounting

Sensor identifier — Unique sensor identifier

1 (default) | positive integer

Specify the unique identifier of the sensor. In a multisensor system, the sensor identifier enables you to distinguish between sensors. When you add a new sensor block to your model, the Sensor identifier of that block is N + 1, where N is the highest Sensor identifier value among the existing sensor blocks in the model.

Example: 2

Parent name — Name of parent vehicle

Scene Origin (default) | vehicle name

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 blocks in your model. If you select Scene Origin, the block places a sensor at the scene origin.

Example: SimulinkVehicle1

Mounting location — Sensor mounting location

Origin (default) | Front bumper | Rear bumper | Right mirror | Left mirror | Rearview mirror | Hood center | Roof center | ...

Sensor mounting location.

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

• When Parent name is the name of a vehicle, 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 Location	Description	Orientation Relative to Vehicle Origin [Roll, Pitch, Yaw] (deg)
Origin	Forward-facing sensor mounted to the vehicle origin, which is on the ground and at the geometric center of the vehicle (see Coordinate Systems for Unreal Engine Simulation in Automated Driving Toolbox)	[0, 0, 0]
Front bumper Front center	Forward-facing sensor mounted to the front bumper	[0, 0, 0]
Rear bumper Rear center	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]

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 above, the yaw angle (the orientation angle) is counterclockwise-positive because you are looking in the negative direction of the axis.

The X-Y-Z mounting 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 to which you mount the sensor. To obtain the X-Y-Z mounting locations for a vehicle type, see the reference page for that vehicle.

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

Specify offset — Specify offset from mounting location

off (default) | on

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.

Relative translation [X, Y, Z] (m) — Translation offset relative to mounting location

[0, 0, 0] (default) | real-valued 1-by-3 vector

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 looking in the forward direction of the vehicle.

• 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 Unreal Engine Simulation in Automated Driving Toolbox.

Example: [0,0,0.01]

Dependencies

To enable this parameter, select Specify offset.

Relative rotation [Roll, Pitch, Yaw] (deg) — Rotational offset relative to mounting location

[0, 0, 0] (default) | real-valued 1-by-3 vector

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 looking in the forward direction of the vehicle.

• 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 Unreal Engine Simulation in Automated Driving Toolbox.

Example: [0,0,10]

Dependencies

To enable this parameter, select Specify offset.

Sample time — Sample time

-1 (default) | positive scalar

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

Detection range (m) — Maximum distance measured by lidar sensor

120 (default) | positive scalar

Maximum distance measured by the lidar sensor, specified as a positive scalar less than or equal to 500. Points outside this range are ignored. Units are in meters.

Range resolution (m) — Resolution of lidar sensor range

0.002 (default) | positive real scalar

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 D_range / 2²⁴, where D_range is the maximum distance measured by the lidar sensor, as specified in the Detection range (m) parameter.

Vertical field of view (deg) — Vertical field of view

40 (default) | positive scalar

Vertical field of view of the lidar sensor, specified as a positive scalar less than or equal to 90. Units are in degrees.

Vertical resolution (deg) — Vertical angular resolution

1.25 (default) | positive scalar

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

Horizontal field of view (deg) — Horizontal field of view

360 (default) | positive scalar

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

Horizontal resolution (deg) — Horizontal angular (azimuth) resolution

0.16 (default) | positive scalar

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

Distance outport — Output distance to measured object points

off (default) | on

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

Reflectivity outport — Output reflectivity of surface materials

off (default) | on

Select this parameter to output the reflectivity of surface materials at the Reflectivity port.

Ground Truth

Output semantic segmentation — Output semantic segmentation map of label IDs

off (default) | on

Select this parameter to output a semantic segmentation map of label IDs at the Labels port.

Output location (m) and orientation (rad) — Output location and orientation of sensor

off (default) | on

Select this parameter to output the translation and rotation of the sensor at the Translation and Rotation ports, respectively.

Tips

• To visualize point clouds that are output by the Point cloud port, you can either:

  • Use a pcplayer object in a MATLAB Function block. You can also use this method to visualize the point cloud with a colormap corresponding to the semantic segmentation labels output by the Labels port. For an example of this visualization setup, see Visualize Sensor Data from Unreal Engine Simulation Environment.

  • Use the Bird's-Eye Scope. For more details, see Visualize Sensor Data from Unreal Engine Simulation Environment.

• 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 Mark Signals for Logging (Simulink).

Version History

Introduced in R2019b

R2024a: Requires Simulink 3D Animation

Simulating models with the Simulation 3D Lidar block requires Simulink 3D Animation.