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poseGraphSolverOptions

Solver options for pose graph optimization

Description

example

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

Examples

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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: [1x74 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 grap 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 therse 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

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Pose graph sovler 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

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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":

 DefaultDescription
MaxIterations300Maximum number of iterations, specified as a positive integer. The optimizer exits after it exceeds this number of iterations.
MaxTime500Maximum time allowed, specified as a positive numeric scalar in seconds. The optimizer exits after it exceeds this time.
FunctionTolerance1e-8Lower 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.
GradientTolerance0.5e-8Lower 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.
StepTolerance1e-12Lower bound on the step size, specified as a scalar. If the norm of the optimization step falls below this value, the optimizer exits.
InitialTrustRegionRadius100Initial 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":

 DefaultDescription
MaxIterations300Maximum number of iterations, specified as a positive integer. The optimizer exits after it exceeds this number of iterations.
MaxTime500Maximum time allowed, specified as a positive numeric scalar in seconds. The optimizer exits after it exceeds this time.
FunctionTolerance1e-8Lower 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.

Introduced in R2020b