Incremental vs Batch FixedLagSmoother

[Joel Truher]

Hi everybody,

I'm making progress on using GTSAM in Java for the FRC 2d localization problem.

I've been using the BatchFixedLagSmoother, using factors for odometry, vision, and gyro, and it works fine in simulation.

This morning I tried swapping in the IncrementalFixedLagSmoother, because I imagined it would be a faster, drop-in replacement.  It did not work well at all.  It produces incorrect, uncertain estimates for awhile, and then aborts with IndeterminantLinearSystemException.  I can make it "work" by supplying the ground-truth pose as the initial value.

Does anyone have advice about the use of these two smoothers?  Is the incremental one supposed to be so sensitive to initial values?  Are there other limitations or best-practices I should be aware of?  Should I just use the batch one?

Thanks!

Joel

[Dellaert, Frank]

Hmmm, would be good to get to the bottom of that. 

One thing you could try when it runs into an indeterminate linear system is to do a batch optimization with Gauss-Newton on exactly the same measurements. If that fails, you have a truly underdetermined system. 

FD

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[Joel Truher]

OK, I've dug a little deeper.  It seems that I completely do not understand ISAM2.

If I set up a simple one-shot problem with GenericProjectionFactor, with a few (tight-prior) landmarks and a single (loose-prior) pose, and appropriate pixel measurements, the Gauss Newton solver works fine.

GaussNewtonOptimizer optimizer(graph(), initial());

Values result = optimizer.optimize();

Giving the same problem to ISAM2 yields nothing useful, it just returns the initial values.

ISAM2 isam2;

isam2.update(graph(), initial());

Values result = isam2.calculateBestEstimate();

I must be doing something terribly wrong here.  Can you advise?

[José Luis Blanco-Claraco]

Hi Joel:

iSAM2 is tricky to use :-)

Try to add additional update() calls before getting the estimate:

ISAM2 isam2;
isam2.update(graph(), initial());
for (int i=0;i<3;i++) {
isam2.update();
}
Values result = isam2.calculateBestEstimate();

Or at least one update().
Also, try reducing the relinearization thresholds:

ISAM2Params params;
params.relinearizeThreshold = 0.01;
params.relinearizeSkip = 1;
ISAM2 isam2(params);

Hope it helps...
JL

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/**
* Jose Luis Blanco-Claraco
* Universidad de Almería - Departamento de Ingeniería
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[Joel Truher]

Oh!  That does indeed make my example work, thank you!

For the larger real case (many poses, many landmarks, many cameras), it still misbehaves in fascinating ways.  I'll come back to it after the batch version is in prod.

Thank you for your help!