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Merge pull request #892 from JuliaRobotics/master
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v0.13.3-rc2
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dehann authored Jul 25, 2022
2 parents 53d843a + 78c37a3 commit de91786
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4 changes: 3 additions & 1 deletion Project.toml
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Expand Up @@ -26,8 +26,8 @@ JSON2 = "2535ab7d-5cd8-5a07-80ac-9b1792aadce3"
KernelDensityEstimate = "2472808a-b354-52ea-a80e-1658a3c6056d"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Manifolds = "1cead3c2-87b3-11e9-0ccd-23c62b72b94e"
NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
Optim = "429524aa-4258-5aef-a3af-852621145aeb"
Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
Expand Down Expand Up @@ -66,13 +66,15 @@ JSON2 = "0.3, 0.4"
KernelDensityEstimate = "0.5"
Manifolds = "0.8"
NLsolve = "4"
NearestNeighbors = "0.4"
Optim = "1"
ProgressMeter = "1"
Reexport = "1"
Requires = "1"
RoME = "0.20"
Rotations = "1.1"
StaticArrays = "1"
StatsBase = "0.33"
TensorCast = "0.4"
TimeZones = "1.3.1, 1.4"
TransformUtils = "0.2.14"
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23 changes: 22 additions & 1 deletion docs/src/concepts/solving_graphs.md
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@@ -1,10 +1,11 @@
# [Solving Graphs](@id solving_graphs)
## Non-parametric Batch Solve

When you have built the graph, you can call the solver to perform inference with the following:

```julia
# Perform inference
tree = solveTree!(fg)
tree = solveTree!(fg) # or solveGraph!
```

The returned Bayes (Junction) `tree` object is described in more detail on [a dedicated documentation page](https://juliarobotics.org/Caesar.jl/latest/principles/bayestreePrinciples/), while `smt` and `hist` return values most closely relate to development and debug outputs which can be ignored during general use. Should an error occur during, the exception information is easily accessible in the `smt` object (as well as file logs which default to `/tmp/caesar/`).
Expand All @@ -13,6 +14,26 @@ The returned Bayes (Junction) `tree` object is described in more detail on [a de
solveTree!
```

## Automatic vs Manual Init

Currently the main automatic initialization technique used by IncrementalInference.jl by delayed propagation of belief on the factor graph. This can be globally or locally controlled via:
```julia
getSolverParams(fg).graphinit = false

# or locally at each addFactor
addFactor!(fg, [:x0;:x1], LinearRelative(Normal()); graphinit=false)
```

Use [`initVariable!`](@ref) if you'd like to force a particular numerical initialization of some or all the variables.
```@docs
initVariable!
```

All the variables can be initialized without solving with:
```@docs
initAll!
```

## Using Incremental Updates (Clique Recycling I)

One of the major features of the MM-iSAMv2 algorithm (implemented by [IncrementalInference.jl](http://www.github.com/JuliaRobotics/IncrementalInference.jl)) is reducing computational load by recycling and marginalizing different (usually older) parts of the factor graph. In order to utilize the benefits of recycing, the previous Bayes (Junction) tree should also be provided as input (see fixed-lag examples for more details):
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2 changes: 1 addition & 1 deletion src/3rdParty/_PCL/services/ICP_Simple.jl
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Expand Up @@ -231,7 +231,7 @@ Notes
- See here for a brief example on [Visualizing Point Clouds](@ref viz_pointcloud_makie).
DevNotes
- TODO switch rigid transfrom to `Caesar._PCL.apply` along with performance considerations, instead of curent `transform!`.
- TODO switch rigid transfrom to `Caesar._PCL.apply` along with performance considerations, instead of current `transform!`.
See also: [`PointCloud`](@ref)
"""
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4 changes: 3 additions & 1 deletion src/images/ScatterAlignPose2.jl
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Expand Up @@ -92,7 +92,9 @@ struct ScatterAlignPose2 <: IIF.AbstractManifoldMinimize
end

"""
ScatterAlignPose3(; mkd1::ManifoldKernelDensity, mkd2::ManifoldKernelDensity, moreoptions...)
ScatterAlignPose3(; cloud1=mkd1::ManifoldKernelDensity,
cloud2=mkd2::ManifoldKernelDensity,
moreoptions...)
Specialization of [`ScatterAlign`](@ref) for [`Pose3`](@ref).
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7 changes: 7 additions & 0 deletions test/pcl/testPointCloud2.jl
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Expand Up @@ -135,6 +135,8 @@ pc_ = Caesar._PCL.apply(M, rPc, pc)
end


if v"1.7" <= VERSION

@testset "PandarXT test point cloud conversion test" begin
##

Expand Down Expand Up @@ -220,6 +222,11 @@ pc_3D = Caesar._PCL.apply(M, rPc, pc)
##
end

else
@error "Skip PointCloud testdata serialization owning to Julia version."
@test_broken false
end



@testset "Test PointCloud on Terrestrial Lidar and ICP_Simple alignment" begin
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