poseGraphSolverOptions

Solver options for pose graph optimization

Since R2020b

Syntax

solverOptions = poseGraphSolverOptions(solverType)

Description

solverOptions = poseGraphSolverOptions(solverType) returns the set of solver options with default values for the specified pose graph solver type.

Examples

Optimize and Trim Loop Closures For 2-D Pose Graphs

Optimize a pose graph based on the nodes and edge constraints. Trim loop closed based on their edge residual errors.

Load the data set that contains a 2-D pose graph. Inspect the poseGraph object to view the number of nodes and loop closures.

load grid-2d-posegraph.mat pg
disp(pg)

  poseGraph with properties:

               NumNodes: 120
               NumEdges: 193
    NumLoopClosureEdges: 74
     LoopClosureEdgeIDs: [120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 ... ] (1x74 double)
        LandmarkNodeIDs: [1x0 double]

Plot the pose graph with IDs off. Red lines indicate loop closures identified in the dataset. The poses in the graph should follow a grid pattern, but show evidence of drift over time.

show(pg,'IDs','off');
title('Original Pose Graph')

Optimize the pose graph using the optimizePoseGraph function. By default, this function uses the "builtin-trust-region" solver. Because the pose graph contains some bad loop closures, the resulting pose graph is actual not desirable.

pgOptim = optimizePoseGraph(pg);
figure;
show(pgOptim);

Look at the edge residual errors for the original pose graph. Large outlier error values at the end indicate bad loop closures.

resErrorVec = edgeResidualErrors(pg);
plot(resErrorVec);
title('Edge Residual Errors by Edge ID')

Certain loop closures should be trimmed from the pose graph based on their residual error. Use the trimLoopClosures function to trim these bad loop closures. Set the maximum and truncation threshold for the trimmer parameters. This threshold is set based on the measurement accuracy and should be tuned for your system.

trimParams.MaxIterations = 100;
trimParams.TruncationThreshold = 25;

solverOptions = poseGraphSolverOptions; 

Use the trimLoopClosures function with the trimmer parameters and solver options.

[pgNew, trimInfo, debugInfo] = trimLoopClosures(pg,trimParams,solverOptions);

From the trimInfo output, plot the loop closures removed from the optimized pose graph. By plotting with the residual errors plot before, you can see the large error loop closures were removed.

removedLCs = trimInfo.LoopClosuresToRemove;

hold on
plot(removedLCs,zeros(length(removedLCs)),'or')
title('Edge Residual Errors and Removed Loop Closures')
legend('Residual Errors', 'Removed Loop Closures')
xlabel('Edge IDs')
ylabel('Edge Residual Error')
hold off

Show the new pose graph with the bad loop closures trimmed.

show(pgNew,"IDs","off");

Input Arguments

solverType — Pose graph solver type

'builtin-trust-region' (default) | 'g2o-levenberg-marquardt'

Pose graph solver type, specified as 'builtin-trust-region' or 'g2o-levenberg-marquardt'.

The function generates a set of solver options with default values for the specified pose graph solver type:

pgSolverTrustRegion = poseGraphSolverOptions('builtin-trust-region')

pgSolverTrustRegion = 

TrustRegion (builtin-trust-region-dogleg) options:

               MaxIterations: 300
                     MaxTime: 10
           FunctionTolerance: 1.0000e-08
           GradientTolerance: 5.0000e-09
               StepTolerance: 1.0000e-12
    InitialTrustRegionRadius: 100
               VerboseOutput: 'off'

pgSolverG2o = poseGraphSolverOptions('g2o-levenberg-marquardt')

pgSolverG2o = 

G2oLevenbergMarquardt (g2o-levenberg-marquardt) options:

        MaxIterations: 300
              MaxTime: 10
    FunctionTolerance: 1.0000e-09
        VerboseOutput: 'off'

Data Types: char | string

Output Arguments

solverOptions — Pose graph solver options

poseGraphSolverOptions parameters

Pose graph solver options, specified as a set of parameters generated by calling the poseGraphSolverOptions function. The function generates a set of solver options with default values for the specified pose graph solver type.

If the solverType input is set to "builtin-trust-region":

	Default	Description
MaxIterations	300	Maximum number of iterations, specified as a positive integer. The optimizer exits after it exceeds this number of iterations.
MaxTime	500	Maximum time allowed, specified as a positive numeric scalar in seconds. The optimizer exits after it exceeds this time.
FunctionTolerance	1e-8	Lower bound on the change in the cost function, specified as a scalar. If the cost function change falls below this value between optimization steps, the optimizer exits.
GradientTolerance	0.5e-8	Lower bound on the norm of the gradient, specified as a scalar. The norm of the gradient is calculated based on the cost function of the optimization. If the norm falls below this value, the optimizer exits.
StepTolerance	1e-12	Lower bound on the step size, specified as a scalar. If the norm of the optimization step falls below this value, the optimizer exits.
InitialTrustRegionRadius	100	Initial trust region radius, specified as a scalar.
VerboseOutput	'off' or 'on'	Display intermediate iteration information on the MATLAB® command line.

If the solver input is set to "g2o-levenberg-marquardt":

	Default	Description
MaxIterations	300	Maximum number of iterations, specified as a positive integer. The optimizer exits after it exceeds this number of iterations.
MaxTime	500	Maximum time allowed, specified as a positive numeric scalar in seconds. The optimizer exits after it exceeds this time.
FunctionTolerance	1e-8	Lower bound on the change in the cost function, specified as a scalar. If the cost function change falls below this value between optimization steps, the optimizer exits.
VerboseOutput	'off' or 'on'	Display intermediate iteration information on the MATLAB command line.

Version History

Introduced in R2020b