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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()

Default variables in IncrementalInference

2D Variables

The current variables types are:

RoME.Point2 — Type
struct Point2 <: InferenceVariable

XY Euclidean manifold variable node softtype.

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.

RoME.DynPoint2 — Type
mutable struct DynPoint2 <: InferenceVariable

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

RoME.DynPose2 — Type
mutable struct DynPose2 <: InferenceVariable

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

3D Variables

RoME.Point3 — Type
struct Point3 <: InferenceVariable

XYZ Euclidean manifold variable node softtype.

Example

p3 = Point3()
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.
RoME.InertialPose3 — Type
mutable struct InertialPose3 <: FunctorPairwise

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(IncrementalInference.FunctorSingleton))));
println("- Pairwise (variable constraints): ")
println.(sort(string.(subtypes(IncrementalInference.FunctorPairwise))));
println("- Pairwise (variable minimization constraints): ")
println.(sort(string.(subtypes(IncrementalInference.FunctorPairwiseMinimize))));

Priors (Absolute Data)

Defaults in IncrementalInference.jl:

IncrementalInference.Prior — Type
struct Prior{T} <: FunctorSingleton

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, P} <: FunctorSingleton

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, Distribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorSingleton

Prior belief on any Polar related variable.

RoME.PriorPoint2 — Type
mutable struct PriorPoint2{T} <: FunctorSingleton

Direction observation information of a Point2 variable.

RoME.PriorPose2 — Type
mutable struct PriorPose2{T} <: FunctorSingleton

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} <: FunctorSingleton

Direction observation information of a Point3 variable.

RoME.PriorPose3 — Type
mutable struct PriorPose3 <: FunctorSingleton

Direct observation information of Pose3 variable type.

Conditional Likelihoods (Relative Data)

Defaults in IncrementalInference.jl:

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

RoME.PolarPolar — Type
mutable struct PolarPolar{T1<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwise

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

RoME.Point2Point2 — Type
mutable struct Point2Point2{D<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwise
RoME.Pose2Point2Bearing — Type
struct Pose2Point2Bearing{B<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwiseMinimize

Single dimension bearing constraint from Pose2 to Point2 variable.

RoME.Pose2Point2BearingRange — Type
mutable struct Pose2Point2BearingRange{B<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}, R<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwiseMinimize

Bearing and Range constraint from a Pose2 to Point2 variable.

RoME.Pose2Point2Range — Type
mutable struct Pose2Point2Range{T} <: FunctorPairwiseMinimize

Range only measurement from Pose2 to Point2 variable.

RoME.Pose2Pose2 — Type
struct Pose2Pose2{T} <: FunctorPairwise

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

Related

Pose3Pose3, Point2Point2, MutablePose2Pose2Gaussian, DynPose2, InertialPose3

RoME.Pose3Pose3 — Type
mutable struct Pose3Pose3 <: FunctorPairwise

Rigid transform factor between two Pose3 compliant variables.

RoME.PriorPose3ZRP — Type
mutable struct PriorPose3ZRP{T1, T2} <: FunctorSingleton

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

RoME.PartialPriorRollPitchZ — Type
mutable struct PartialPriorRollPitchZ{T1, T2} <: FunctorSingleton

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

RoME.PartialPose3XYYaw — Type
mutable struct PartialPose3XYYaw{T1, T2} <: FunctorPairwise

Partial factor between XY and Yaw of two Pose3 variables.

To be deprecated: use Pose3Pose3XYYaw instead.

RoME.Pose3Pose3XYYaw — Type
mutable struct Pose3Pose3XYYaw{T1, T2} <: FunctorPairwise

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.