wheelEncoderAckermann

Simulate wheel encoder sensor readings for Ackermann vehicle

Since R2020b

Description

The wheelEncoderAckermann System object™ computes wheel encoder tick readings based on the pose input of an Ackermann vehicle.

To obtain the encoder tick readings:

1. Create the wheelEncoderAckermann object and set its properties.

2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

Creation

Syntax

encoder = wheelEncoderAckermann

encoder= wheelEncoderAckermann(Name,Value)

Description

encoder = wheelEncoderAckermann creates a wheelEncoderAckermann System object, encoder.

encoder= wheelEncoderAckermann(Name,Value) sets properties for the encoder using one or more name-value pairs. For example, wheelAckermann('SampleRate',120) sets the sample rate of the encoder to 120 Hz. Unspecified properties have default values. Enclose each property name in quotes.

Properties

Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

SampleRate — Sample rate of encoder

100 (default) | positive scalar

Sample rate of the encoder, specified as a positive scalar in Hz.

Example: 'SampleRate',100

Data Types: double

TicksPerRevolution — Number of encoder ticks per wheel revolution

[2048 2048 2048 2048] (default) | four-element vector of positive integers

Number of encoder ticks per wheel revolution, specified as a four-element vector of positive integers. The first, second, third, and fourth elements are for the back-left, back-right, front-left, and front-right wheels, respectively.

Data Types: double

WheelRadius — Wheel radius

[0.35 0.35 0.35 0.35] (default) | four-element vector of positive scalars

Wheel radius, specified as a four-element vector of positive scalars in meters. The first, second, third, and fourth elements are for the back-left, back-right, front-left, and front-right wheels, respectively.

Data Types: double

WheelRadiusBias — Bias of wheel radius

[0 0 0 0] (default) | four-element vector of scalars

Bias of the wheel radius, specified as a four-element vector of scalars in meters. The first, second, third, and fourth elements are for the back-left, back-right, front-left, and front-right wheels, respectively.

Data Types: double

WheelPositionAccuracy — Standard deviation of wheel position error

[0 0 0 0] (default) | four-element vector of nonnegative scalars

Standard deviation of wheel position error, specified as a four-element vector of nonnegative scalars in radians. The first, second, third, and fourth elements are for the back-left, back-right, front-left, and front-right wheels, respectively.

Data Types: double

SlipRatio — Slip or skid ratio of wheel

[0 0 0 0] (default) | four-element vector of scalars

Slip or skid ratio of the wheel, specified as a four-element vector of scalars in which each scalar is larger than or equal to –1. The first, second, third, and fourth elements are for the back-left, back-right, front-left, and front-right wheels, respectively.

• For a wheel that slips (over rotation), specify it as a positive value. A higher value denotes more slipping.

• For a wheel that skids (under rotation), specify it as a negative value larger than or equal to –1. A lower value denotes more skidding. For a wheel that does not rotate, specify it as –1.

Data Types: double

TrackWidth — Distance between wheel axles

[1.572 1.572] (default) | two-element vector of positive scalars

Distance between the wheel axles, specified as a two-element vector of positive scalars in meters. The first element is for the back track, and the second element is for the front track.

Data Types: double

TrackWidthBias — Bias of track width

0 (default) | two-element vector of scalars

Bias of track width, specified as a two-element vector of scalars in meters. The first element is for the back track, and the second element is for the front track.

Data Types: double

WheelBase — Distance between front and rear axles

2.818 (default) | positive scalar

Distance between the front and the rear axles, specified as a positive scalar in meters.

Data Types: double

RandomStream — Random number source

'Global stream' (default) | 'mt19937ar with seed'

Random number source, specified as a character vector or string:

• 'Global stream' –– Random numbers are generated using the current global random number stream.

• 'mt19937ar with seed' –– Random numbers are generated using the mt19937ar algorithm with the seed specified by the Seed property.

Data Types: char | string

Seed — Initial seed

67 (default) | nonnegative integer

Initial seed of an mt19937ar random number generator algorithm, specified as a nonnegative integer.

Dependencies

To enable this property, set RandomStream to 'mt19937ar with seed'.

Usage

Syntax

ticks = encoder(velocity,angularVelocity,orientation)

Description

ticks = encoder(velocity,angularVelocity,orientation) return the wheel tick readings, ticks, form velocity, angular velocity, and orientation information.

Input Arguments

velocity — Velocity of vehicle

N-by-3 matrix of scalars

Velocity of the vehicle in the local navigation frame, specified as an N-by-3 matrix of scalars in m/s. N is the number of samples.

angularVelocity — Angular velocity of vehicle

N-by-3 matrix of scalars

Angular velocity of the vehicle in the local navigation frame, specified as an N-by-3 matrix of scalars in rad/s. N is the number of samples.

orientation — orientation of vehicle

N-element vector of quaternion | 3-by-3-by-N array of rotation matrices

Orientation of the vehicle in the local navigation frame, specified as an N-element vector of quaternion or a 3-by-3-by-N array of rotation matrices. N is the number of samples. Each quaternion or rotation matrix is a frame rotation from the local navigation coordinate system to the current vehicle body coordinate system.

Output Arguments

ticks — Number of wheel ticks per time step

N-by-4 matrix of nonnegative integers

Number of wheel ticks the vehicle moved per time step, returned as an N-by-4 matrix of nonnegative integers. N is the number of samples. The first, second, third, and fourth columns are for the back-left, back-right, front-left, and front-right wheels, respectively.

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

Common to All System Objects

clone	Create duplicate System object
step	Run System object algorithm
release	Release resources and allow changes to System object property values and input characteristics
reset	Reset internal states of System object
isLocked	Determine if System object is in use

Examples

Generate Wheel Ticks from Ackermann Vehicle Pose

Create the wheel encoder sensor.

encoder = wheelEncoderAckermann;

Define poses of the vehicle.

orient = [quaternion([60 0 0],'eulerd','ZYX','frame'); quaternion([45 0 0], 'eulerd', 'ZYX', 'frame')];
vel = [1 0 0; 0 1 0];
angvel = [0 0 0.2; 0 0 0.1];

Generate wheel ticks from the poses.

ticks = encoder(vel,angvel,orient)

ticks = 2×4

     3     6     6     8
     6     7     6     7

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

See System Objects in MATLAB Code Generation (MATLAB Coder).

Version History

Introduced in R2020b