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odometryMotionModel

Create an odometry motion model

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Description

odometryMotionModel creates an odometry motion model object for differential drive vehicles. This object contains specific motion model parameters. You can use this object to specify the motion model parameters in the monteCarloLocalization object.

This motion model assumes that the vehicle makes pure rotation and translation motions to travel from one location to the other. The model propagates points for either forward or backwards motion based on these motion patterns. The elements of the Noise property refer to the variance in the motion. To see the effect of changing the noise parameters, use showNoiseDistribution.

Creation

Syntax

omm = odometryMotionModel

Description

omm = odometryMotionModel creates an odometry motion model object for differential drive vehicles.

example

Properties

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Gaussian noise for vehicle motion, specified as a 4-element vector. This property represents the variance parameters for Gaussian noise applied to vehicle motion. The elements of the vector correspond to the following errors in order:

  • Rotational error due to rotational motion

  • Rotational error due to translational motion

  • Translational error due to translation motion

  • Translational error due to rotational motion

This property is read-only.

Type of the odometry motion model, returned as 'DifferentialDrive'. This read-only property indicates the type of odometry motion model being used by the object.

Object Functions

showNoiseDistributionDisplay noise parameter effects

Examples

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Open Live Script

This example shows how to use the odometryMotionModel class to predict the pose of a vehicle. An odometryMotionModel object contains the motion model parameters for a differential drive vehicle. Use the object to predict the pose of a vehicle based on its current and previous poses and the motion model parameters.

Create odometry motion model object.

motionModel = odometryMotionModel;

Define previous poses and the current odometry reading. Each pose prediction corresponds to a row in previousPoses vector.

previousPoses =  rand(10,3);
currentOdom = [0.1 0.1 0.1];

The first call to the object initializes values and returns the previous poses as the current poses.

currentPoses = motionModel(previousPoses, currentOdom);

Subsequent calls to the object with updated odometry poses returns the predicted poses based on the motion model.

currentOdom = currentOdom + [0.1 0.1 0.05];
predPoses = motionModel(previousPoses, currentOdom);
Open Live Script

This example shows how to visualize the effect of different noise parameters on the odometryMotionModel class. An odometryMotionModel object contains the motion model noise parameters for a differential drive vehicle. Use showNoiseDistribution to visualize how changing these values affect the distribution of predicted poses.

Create a motion model object.

motionModel = odometryMotionModel;

Show the distribution of particles with the existing noise parameters. Each particle is a hypothesis for the predicted pose.

showNoiseDistribution(motionModel);

Figure Odometry Motion Model contains an axes object. The axes object with title Noise Parameters: [0.2 0.2 0.2 0.2], xlabel X [meters], ylabel Y [meters] contains 4 objects of type line. One or more of the lines displays its values using only markers These objects represent Robot initial pose, Robot final pose, Samples at final pose.

Show the distribution with a specified odometry pose change and number of samples. The change in odometry is used as the final pose with hypotheses distributed around based on the Noise parameters.

showNoiseDistribution(motionModel, ...
            'OdometryPoseChange', [0.5 0.1 0.25], ...
            'NumSamples', 1000);

Figure Odometry Motion Model contains an axes object. The axes object with title Noise Parameters: [0.2 0.2 0.2 0.2], xlabel X [meters], ylabel Y [meters] contains 4 objects of type line. One or more of the lines displays its values using only markers These objects represent Robot initial pose, Robot final pose, Samples at final pose.

Change the Noise parameters and visualize the effects. Use the same odometry pose change and number of samples.

 motionModel.Noise = [0.2 1 0.2 1];
 
 showNoiseDistribution(motionModel, ...
            'OdometryPoseChange', [0.5 0.1 0.25], ...
            'NumSamples', 1000);

Figure Odometry Motion Model contains an axes object. The axes object with title Noise Parameters: [0.2 1 0.2 1], xlabel X [meters], ylabel Y [meters] contains 4 objects of type line. One or more of the lines displays its values using only markers These objects represent Robot initial pose, Robot final pose, Samples at final pose.

Limitations

If you make changes to your motion model after using it with the monteCarloLocalization object, call release on that object beforehand. For example:

mcl = monteCarloLocalization; 
[isUpdated,pose,covariance] = mcl(ranges,angles); 
release(mcl) 
mcl.MotionModel.Noise = [0.25 0.25 0.4 0.4];

References

[1] Thrun, Sebatian, Wolfram Burgard, and Dieter Fox. Probabilistic Robotics. MIT Press, 2005.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced in R2019b

See Also

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