optimizePoses

Optimize absolute poses using relative pose constraints

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Syntax

vSetOptim = optimizePoses(vSet)
vSetOptim = optimizePoses(vSet,Name,Value)

Description

example

vSetOptim = optimizePoses(vSet) returns a point cloud view set whose absolute poses are optimized. vSetOptim and vSet are pcviewset objects.

The optimizePoses function performs pose graph optimization on the absolute poses for the Views in the view set using the relative pose constraints established by the Connections property. You can use optimizePoses to correct drift in odometry after detecting loop closures.

vSetOptim = optimizePoses(vSet,Name,Value) specifies options using one or more name-value pair arguments. For example, 'Tolerance',0.2 sets the tolerance of the optimization cost function to 0.2.

Examples

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Open Live Script

Create a view set.

vSet = pcviewset;

Add four nodes and specify absolute poses. 

absPoses = repelem(rigid3d, 4, 1);   

absPoses(1).Translation = [ 0   0 0];
absPoses(2).Translation = [ 1   0 0];
absPoses(3).Translation = [ 2   0 0];
absPoses(4).Translation = [ 0.1 0 0];

vSet = addView(vSet, 1, absPoses(1));
vSet = addView(vSet, 2, absPoses(2));
vSet = addView(vSet, 3, absPoses(3));
vSet = addView(vSet, 4, absPoses(4));

Define 4 edges, 3 odometry and 1 loop closure.

relPoses = repelem(rigid3d, 4, 1);

relPoses(1).Translation = [ 1   0 0];
relPoses(2).Translation = [ 1   0 0];
relPoses(3).Translation = [-1.9 0 0];
relPoses(4).Translation = [ 0.2 0 0];

vSet = addConnection(vSet, 1, 2, relPoses(1)); % odometry
vSet = addConnection(vSet, 2, 3, relPoses(2)); % odometry
vSet = addConnection(vSet, 3, 4, relPoses(3)); % odometry
vSet = addConnection(vSet, 4, 1, relPoses(4)); % loop closure

Optimize view set. 

vSetOptim = optimizePoses(vSet);

DIsplay original and optimized locations. 

disp('Original absolute translations:')
Original absolute translations:

disp(vertcat(vSet.Views.AbsolutePose.Translation))
         0         0         0
    1.0000         0         0
    2.0000         0         0
    0.1000         0         0

disp('Optimized absolute translations:')
Optimized absolute translations:

disp(vertcat(vSetOptim.Views.AbsolutePose.Translation))
         0         0         0
    0.9250         0         0
    1.8500         0         0
   -0.1250         0         0

Input Arguments

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Point cloud view set, specified as a pcviewset object.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'MaxIterations',300 sets the maximum number of iterations to 300.

Maximum number of iterations before the function terminates optimization, specified as the comma-separated pair consisting of 'MaxIterations' and a positive integer. Increase this value for greater accuracy in the results. Decrease this value for faster results.

Tolerance of the optimization cost function between two consecutive iterations, specified as the comma-separated pair consisting of 'Tolerance' and a positive scalar. If the cost function changes by less than the 'Tolerance' value between two consecutive iterations, the function terminates optimization.

Display progress information, specified as the comma-separated pair consisting of Verbose and a numeric or logical 0 (false) or 1 (true). To display the progress information, set 'Verbose' to true.

Output Arguments

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Point cloud view set that contains optimized absolute poses, specified as a pcviewset object.

Tips

  • To update a view set with optimized poses, use the updateView object function.

  • The optimizePoses object function holds the first view fixed.

Algorithms

The optimizePoses function uses the Levenberg-Marquardt optimization algorithm with sparse Cholesky decomposition from the general (hyper) graph optimization (G2o) library, [1].

References

[1] Kümmerle, Rainer, Giorgio Grisetti, Hauke Strasdat, Kurt Konolige, and Wolfram Burgard. “G2o: A General Framework for Graph Optimization.” In 2011 IEEE International Conference on Robotics and Automation, 3607–13, 2011. https://doi.org/10.1109/ICRA.2011.5979949.

See Also

Functions

Objects

Introduced in R2020a

Computer Vision Toolbox Documentation

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