v0.24.4 RC1

Project.toml

@@ -2,7 +2,7 @@ name = "RoME"
 uuid = "91fb55c2-4c03-5a59-ba21-f4ea956187b8"
 keywords = ["SLAM", "state-estimation", "MM-iSAM", "MM-iSAMv2", "inference", "robotics"]
 desc = "Non-Gaussian simultaneous localization and mapping"
-version = "0.24.3"
+version = "0.24.4"
 
 [deps]
 ApproxManifoldProducts = "9bbbb610-88a1-53cd-9763-118ce10c1f89"
@@ -48,15 +48,19 @@ RoMEImageIOExt = "ImageIO"
 
 [compat]
 ApproxManifoldProducts = "0.8"
+CameraModels = "0.2"
 CoordinateTransformations = "0.5, 0.6"
 Dates = "1.10"
 DelimitedFiles = "1"
+DifferentialEquations = "7"
 Distributed = "1.10"
-DistributedFactorGraphs = "0.23"
+DistributedFactorGraphs = "0.23, 0.24"
 Distributions = "0.24, 0.25"
 DocStringExtensions = "0.8, 0.9"
 FileIO = "1"
+Flux = "0.14"
 ImageCore = "0.9, 0.10"
+ImageIO = "0.6"
 IncrementalInference = "0.35"
 Interpolations = "0.14, 0.15"
 KernelDensityEstimate = "0.5.1, 0.6"

README.md

@@ -9,7 +9,7 @@
 
 Robot Motion Estimate (RoME.jl) is part of the overall [Caesar.jl][cjl-url] and provides a set of graph variables, factors, and utility features for robotics-related navigation, tracking, and mapping (i.e. SLAM).  RoME.jl helps build front-ends using the [Multi-modal iSAM] backend solver which is implemented over at [IncrementalInference.jl][iif-url].  See [the related references of interest here](http://www.juliarobotics.org/Caesar.jl/latest/refs/literature/).  Most notably, this package provides common navigation-type variables and factors to be included in more general [DistributedFactorGraphs.jl](https://github.com/JuliaRobotics/DistributedFactorGraphs.jl) graph objects.
 
-[NavAbility.io](http://www.navability.io) helps the with administration and support of the Caesar.jl community, please reach out for any additional information (info@navability.io) or via the caesarjl Slack badge-link above.
+[NavAbility(TM) by WhereWhen.ai](http://www.wherewhen.ai) helps the with administration and support of the Caesar.jl community, please reach out for any additional information (info@wherewhen.ai) or via the caesarjl Slack badge-link above.
 ## Installation
 
 You can directly install with:

ext/RoMEFluxExt.jl

@@ -1,6 +1,6 @@
 module RoMEFluxExt
 
-@info "RoME.jl is loading extension functionality related to Flux.jl."
+# @info "RoME.jl is loading extension functionality related to Flux.jl."
 
 using Flux
 

ext/RoMEImageIOExt.jl

@@ -2,7 +2,7 @@ module RoMEImageIOExt
 
 # ScalarField functions related to Images.jl
 
-@info "RoME.jl is loading extension functionality related ImageCore.jl and ImageIO.jl"
+# @info "RoME.jl is loading extension functionality related ImageCore.jl and ImageIO.jl"
 
 using ImageIO
 using ImageCore

src/RoME.jl

@@ -32,6 +32,7 @@ using Manifolds: hat, ProductGroup, ProductManifold, SpecialEuclidean, SpecialOr
 import Manifolds: project, project!, identity_element
 
 import Rotations as _Rot
+import Rotations: ⊕, ⊖ # TODO deprecate
 
 export SpecialOrthogonal, SpecialEuclidean
 export submanifold_component

src/factors/Pose3Pose3.jl

@@ -16,6 +16,12 @@ Pose3Pose3(::UniformScaling) = Pose3Pose3()
 
 function (cf::CalcFactor{<:Pose3Pose3})(X, p::ArrayPartition{T}, q) where T
     M = getManifold(Pose3)
+    # X: p_Xq̂
+    # p: w_H_p
+    # q: w_H_q
+    # ̂q: w_H_̂q = w_H_p * exp_0(p_Xq̂)
+    # w_H_̂q = Manifolds.compose(M, w_H_p, exp(M, getPointIdentity(M), p_Xq̂))
+
     q̂ = Manifolds.compose(M, p, exp(M, getPointIdentity(M), X))
 
     Xc::SVector{6,T} = get_coordinates(M, q, log(M, q, q̂), DefaultOrthogonalBasis())
@@ -85,4 +91,14 @@ function (cf::CalcFactor{<:Pose3Pose3UnitTrans})(X, p::ArrayPartition{T}, q) whe
     q̂ = Manifolds.compose(M, p, exp(M, getPointIdentity(M), X))
     Xc::SVector{6,T} = get_coordinates(M, q, log(M, q, q̂), DefaultOrthogonalBasis())
     return SVector{6,T}(normalize(Xc[1:3])..., Xc[4:6]...)
+end
+
+Base.@kwdef struct PackedPose3Pose3UnitTrans <: AbstractPackedFactor
+  Z::PackedSamplableBelief
+end
+function convert(::Type{Pose3Pose3UnitTrans}, packed::PackedPose3Pose3UnitTrans)
+  return Pose3Pose3UnitTrans( convert(SamplableBelief, packed.Z) )
+end
+function convert(::Type{PackedPose3Pose3UnitTrans}, obj::Pose3Pose3UnitTrans)
+  return PackedPose3Pose3UnitTrans( convert(PackedSamplableBelief, obj.Z) )
 end