Variables in Caesar.jl

You can check for the latest variable types by running the following in your terminal:

using RoME, Caesar
subtypes(IncrementalInference.InferenceVariable)
IncrementalInference.getCurrentWorkspaceVariables()

Note

More variables and factors exists, but are not yet included in the standard library. It is fairly straight forward to build your own out-of-library factors, see page Creating New Variables and Factors for more details.

Default variables in IncrementalInference

IncrementalInference.ContinuousScalar — Type

struct ContinuousScalar <: InferenceVariable

Most basic continuous scalar variable in a ::DFG.AbstractDFG object.

DevNotes

TODO Consolidate with ContinuousEuclid{1}

source

IncrementalInference.ContinuousEuclid — Type

ContinuousEuclid{N}

Continuous Euclidean variable of dimension N.

2D Variables

The current variables types are:

RoME.Point2 — Type

struct Point2 <: InferenceVariable

XY Euclidean manifold variable node softtype.

source

RoME.Pose2 — Type

struct Pose2 <: InferenceVariable

Pose2 is a SE(2) mechanization of two Euclidean translations and one Circular rotation, used for general 2D SLAM.

source

RoME.DynPoint2 — Type

struct DynPoint2 <: InferenceVariable

Dynamic point in 2D space with velocity components: x, y, dx/dt, dy/dt

source

RoME.DynPose2 — Type

struct DynPose2 <: InferenceVariable

Dynamic pose variable with velocity components: x, y, theta, dx/dt, dy/dt

source

3D Variables

RoME.Point3 — Type

struct Point3 <: InferenceVariable

XYZ Euclidean manifold variable node softtype.

Example

p3 = Point3()

source

RoME.Pose3 — Type

struct Pose3 <: InferenceVariable

Pose3 is currently a Euler angle mechanization of three Euclidean translations and three Circular rotation.

Future:

Work in progress on AMP3D for proper non-Euler angle on-manifold operations.
TODO the AMP upgrade is aimed at resolving 3D to Quat/SE3/SP3 – current Euler angles will be replaced

source

RoME.InertialPose3 — Type

mutable struct InertialPose3 <: AbstractRelativeRoots

Inertial Odometry version of preintegration procedure and used as a factor between InertialPose3 types for inertial navigation in factor graphs.

Note

Please open an issue with JuliaRobotics/RoME.jl for specific requests, problems, or suggestions. Contributions are also welcome. There might be more variable types in Caesar/RoME/IIF not yet documented here.

Factors in Caesar.jl

You can check for the latest factor types by running the following in your terminal:

using RoME, Caesar
println("- Singletons (priors): ")
println.(sort(string.(subtypes(IIF.AbstractPrior))));
println("- Pairwise (variable constraints): ")
println.(sort(string.(subtypes(IIF.AbstractRelativeRoots))));
println("- Pairwise (variable minimization constraints): ")
println.(sort(string.(subtypes(IIF.AbstractRelativeMinimize))));

Priors (Absolute Data)

Defaults in IncrementalInference.jl:

IncrementalInference.Prior — Type

struct Prior{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractPrior

Default prior on all dimensions of a variable node in the factor graph. Prior is not recommended when non-Euclidean dimensions are used in variables.

IncrementalInference.PartialPrior — Type

struct PartialPrior{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, P<:Tuple} <: AbstractPrior

Partial prior belief (absolute data) on any variable, given <:SamplableBelief and which dimensions of the intended variable.

Some of the most common priors (unary factors) in Caesar.jl/RoME.jl include:

RoME.PriorPolar — Type

mutable struct PriorPolar{T1<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractPrior

Prior belief on any Polar related variable.

RoME.PriorPoint2 — Type

mutable struct PriorPoint2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractPrior

Direction observation information of a Point2 variable.

RoME.PriorPose2 — Type

mutable struct PriorPose2{T} <: AbstractPrior

Introduce direct observations on all dimensions of a Pose2 variable:

Example:

PriorPose2( MvNormal([10; 10; pi/6.0], Matrix(Diagonal([0.1;0.1;0.05].^2))) )

RoME.PriorPoint3 — Type

mutable struct PriorPoint3{T} <: AbstractPrior

Direction observation information of a Point3 variable.

RoME.PriorPose3 — Type

mutable struct PriorPose3{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractPrior

Direct observation information of Pose3 variable type.

Relative Likelihoods (Relative Data)

Defaults in IncrementalInference.jl:

IncrementalInference.LinearRelative — Type

struct LinearRelative{N, T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

Default linear offset between two scalar variables.

\[X_2 = X_1 + η_Z\]

Existing n-ary factors in Caesar.jl/RoME.jl/IIF.jl include:

RoME.PolarPolar — Type

mutable struct PolarPolar{T1<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

Linear offset factor of IIF.SamplableBelief between two Polar variables.

RoME.Point2Point2 — Type

mutable struct Point2Point2{D<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

RoME.Pose2Point2 — Type

struct Pose2Point2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Bearing and Range constraint from a Pose2 to Point2 variable.

RoME.Pose2Point2Bearing — Type

struct Pose2Point2Bearing{B<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Single dimension bearing constraint from Pose2 to Point2 variable.

RoME.Pose2Point2BearingRange — Type

mutable struct Pose2Point2BearingRange{B<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, R<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Bearing and Range constraint from a Pose2 to Point2 variable.

RoME.Pose2Point2Range — Type

mutable struct Pose2Point2Range{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Range only measurement from Pose2 to Point2 variable.

RoME.Pose2Pose2 — Type

struct Pose2Pose2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

Rigid transform between two Pose2's, assuming (x,y,theta).

Pose3Pose3, Point2Point2, MutablePose2Pose2Gaussian, DynPose2, InertialPose3

RoME.DynPoint2VelocityPrior — Type

mutable struct DynPoint2VelocityPrior{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractPrior

RoME.DynPoint2DynPoint2 — Type

mutable struct DynPoint2DynPoint2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

RoME.VelPoint2VelPoint2 — Type

mutable struct VelPoint2VelPoint2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

RoME.Point2Point2Velocity — Type

mutable struct Point2Point2Velocity{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

RoME.DynPose2VelocityPrior — Type

mutable struct DynPose2VelocityPrior{T1, T2} <: AbstractPrior

RoME.VelPose2VelPose2 — Type

mutable struct VelPose2VelPose2{T1<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

RoME.DynPose2Pose2 — Type

mutable struct DynPose2Pose2{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

RoME.Pose3Pose3 — Type

mutable struct Pose3Pose3{T<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeRoots

Rigid transform factor between two Pose3 compliant variables.

RoME.PriorPose3ZRP — Type

mutable struct PriorPose3ZRP{T1, T2} <: AbstractPrior

Partial prior belief on Z, Roll, and Pitch of a Pose3.

RoME.PartialPriorRollPitchZ — Type

mutable struct PartialPriorRollPitchZ{T1, T2} <: AbstractPrior

Partial prior belief on Roll Pitch and Z of a Pose3 variable.

RoME.PartialPose3XYYaw — Type

mutable struct PartialPose3XYYaw{T1<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Partial factor between XY and Yaw of two Pose3 variables.

To be deprecated: use Pose3Pose3XYYaw instead.

RoME.Pose3Pose3XYYaw — Type

mutable struct Pose3Pose3XYYaw{T1<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, ManifoldKernelDensity, Distribution, IncrementalInference.FluxModelsDistribution}} <: AbstractRelativeMinimize

Partial factor between XY and Yaw of two Pose3 variables.

Extending Caesar with New Variables and Factors

A question that frequently arises is how to design custom variables and factors to solve a specific type of graph. One strength of Caesar is the ability to incorporate new variables and factors at will. Please refer to Adding Factors for more information on creating your own factors.