Parametric Solve (Experimental)

Batch

IncrementalInference.solveFactorGraphParametric — Function

solveFactorGraphParametric(fg; useCalcFactor, solvekey, autodiff, algorithm, algorithmkwargs, options)

Batch solve a Gaussian factor graph using Optim.jl. Parameters can be passed directly to optim. Notes:

Only :Euclid and :Circular manifolds are currently supported, own manifold are supported with algorithmkwargs (code may need updating though)

Missing docstring.

Missing docstring for solveFactorGraphParametric!. Check Documenter's build log for details.

Defining Factors to Support a Parametric Solution (Experimental)

Factor that supports a parametric solution, with supported distributions (such as Normal and MvNormal), can be used in a parametric batch solver solveFactorGraphParametric.

`getParametricMeasurement`

Missing docstring.

Missing docstring for getParametricMeasurement. Check Documenter's build log for details.

getParametricMeasurement defaults to looking for a supported distribution in field .Z followed by .z. Therefore, if the factor uses this fieldname, getParametricMeasurement does not need to be extended.

For example the Z field will be used by default in MyFactor from above.

struct MyFactor{T <: SamplableBelief} <: IIF.AbstractRelativeRoots
  Z::T
end

An example of where implementing getParametricMeasurement is needed can be found in the RoME factor Pose2Point2BearingRange

import getParametricMeasurement
function getParametricMeasurement(s::Pose2Point2BearingRange{<:Normal, <:Normal})

  meas = [mean(s.bearing), mean(s.range)]
  iΣ = [1/var(s.bearing)             0;
                      0  1/var(s.range)]

  return meas, iΣ
end

The Factor

The factor is evaluated in a cost function using the Mahalanobis distance and the measurement should therefore match the residual returned.

Optimization

solveFactorGraphParametric uses Optim.jl. The factors that are supported should have a gradient and Hessian available/exists and therefore it makes use of TwiceDifferentiable. Full control of Optim's setup is possible with keyword arguments.