diff --git a/test/inertial/testIMUCases.jl b/test/inertial/testIMUCases.jl new file mode 100644 index 00000000..443b1d78 --- /dev/null +++ b/test/inertial/testIMUCases.jl @@ -0,0 +1,222 @@ + +using Dates +using RoME +using CSV + +df = CSV.read(@__DIR__() * "/testdata/IMUCase1.csv", DataFrame) +σ_a = 5e-4 # noise density m/s²/√Hz +σ_ω = 2e-6 # noise density rad/√Hz +Σy = diagm([ones(3)*σ_a^2; ones(3)*σ_ω^2]) + + +a_b = SA[0.,0,0] +ω_b = SA[0.,0,0] + +accels = map(SVector, zip(df.nax, df.nay, df.naz)) +gyros = map(SVector, zip(df.nwx, df.nwy, df.nwz)) +timestamps = df.time + +pidx = range(1; step=100, stop=length(timestamps)) +factors = map(zip(pidx[1:end-1], pidx[2:end])) do (fr,to) + r = range(fr,to-1) + RoME.IMUDeltaFactor( + SVector{3,Float64}.(accels[r]), + SVector{3,Float64}.(gyros[r]), + ones(length(r))*Ts, + Σy, + a_b, + ω_b + ) +end + +times = timestamps[pidx] + +fg = initfg() +fg.solverParams.graphinit = false + +foreach(enumerate(Nanosecond.(times * 10^9))) do (i,nanosecondtime) + addVariable!(fg, Symbol("x",i-1), Pose3; nanosecondtime) + addVariable!(fg, Symbol("v",i-1), Position3; nanosecondtime) +end + +addFactor!(fg, [:x0], PriorPose3(MvNormal([1.0, 1, 1, 0, 0, 0], diagm(ones(6)*1e-3^2)))) +# addFactor!(fg, [:v0], PriorPoint3(MvNormal([0.0, 0, 0], diagm(ones(3)*1e-3)))) + +# addFactor!(fg, [:x9], PriorPose3(MvNormal([1.0, 1, 1.0, 0, 0, 0], diagm(ones(6)*1e-3^2)))) +# addFactor!(fg, [:v9], PriorPoint3(MvNormal([0.0, 0, 0], diagm(ones(3)*1e-3)))) + +for l in ls(fg, r"v\d") + addFactor!(fg, [l], PriorPoint3(MvNormal([0.0, 0, 0], diagm(ones(3)*1e-3)))) +end + +# Variable for bias +addVariable!(fg, :b, Position{6}) + +for (i,fac) in enumerate(factors) + frx = Symbol("x",i-1) + frv = Symbol("v",i-1) + tox = Symbol("x",i) + tov = Symbol("v",i) + if exists(fg, :b) + addFactor!(fg, [frx,frv, tox, tov, :b], fac) + else + addFactor!(fg, [frx,frv, tox, tov], fac) + end +end + + +debug = [:Iteration, :Change, " | ", :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :damping_term, "\n", :Stop] +debug = [:Iteration, :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :last_step_successful, "\n", :Stop] +stopping_criterion=StopAfterIteration(1000) | StopWhenGradientNormLess(1e-12) | StopWhenStepsizeLess(1e-12) + +@time IIF.solveGraphParametric!(fg; stopping_criterion, debug, is_sparse=false, damping_term_min=1e-12, expect_zero_residual=false); + +vnd = getVariableSolverData(fg, :b, :parametric) +vnd.val + +## Test Case 2 +df = CSV.read(@__DIR__() * "/testdata/IMUCase2.csv", DataFrame; limit = 3001) +# df = CSV.read(@__DIR__() * "/testdata/IMUCase2.csv", DataFrame) +σ_a = 0.037/60*sqrt(100) # noise density m/s²/√Hz - 0.037 m/s/√hr +σ_ω = 0.15*pi*60/180/3600*sqrt(100) # noise density rad/√Hz - 0.15 deg/√hr +Σy = diagm([ones(3)*σ_a^2; ones(3)*σ_ω^2]) + +a_b = SA[0.,0,0] +ω_b = SA[0.,0,0] + +accels = map(SVector, zip(df.nax, df.nay, df.naz)) +gyros = map(SVector, zip(df.nwx, df.nwy, df.nwz)) +timestamps = df.time + +pidx = range(1; step=100, stop=length(timestamps)) +factors = map(zip(pidx[1:end-1], pidx[2:end])) do (fr,to) + r = range(fr,to-1) + RoME.IMUDeltaFactor( + SVector{3,Float64}.(accels[r]), + SVector{3,Float64}.(gyros[r]), + ones(length(r))*Ts, + Σy, + a_b, + ω_b + ) +end + +times = timestamps[pidx] + +fg = initfg() +fg.solverParams.graphinit = false + +foreach(enumerate(Nanosecond.(times * 10^9))) do (i,nanosecondtime) + addVariable!(fg, Symbol("x",i-1), Pose3; nanosecondtime) + addVariable!(fg, Symbol("v",i-1), Position3; nanosecondtime) +end + +addFactor!(fg, [:x0], PriorPose3(MvNormal([1.0, 1, 1, 0, 0, 0], diagm(ones(6)*1e-3^2)))) +addFactor!(fg, [sortDFG(ls(fg, r"^x"))[end]], PriorPose3(MvNormal([1.0, 1, 1.0, 0, 0, 0], diagm(ones(6)*1e-3^2)))) + +for l in ls(fg, r"v\d") + addFactor!(fg, [l], PriorPoint3(MvNormal([0.0, 0, 0], diagm(ones(3)*1e-3)))) +end + +# Variable for bias +addVariable!(fg, :b, Position{6}) + +for (i,fac) in enumerate(factors) + frx = Symbol("x",i-1) + frv = Symbol("v",i-1) + tox = Symbol("x",i) + tov = Symbol("v",i) + if exists(fg, :b) + addFactor!(fg, [frx,frv, tox, tov, :b], fac) + else + addFactor!(fg, [frx,frv, tox, tov], fac) + end +end + + +debug = [:Iteration, :Change, " | ", :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :damping_term, "\n", :Stop] +debug = [:Iteration, :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :last_step_successful, "\n", :Stop] +stopping_criterion=StopAfterIteration(1000) | StopWhenGradientNormLess(1e-12) | StopWhenStepsizeLess(1e-12) + +@time IIF.solveGraphParametric!(fg; stopping_criterion, debug, is_sparse=false, damping_term_min=1e-12, expect_zero_residual=false); + +vnd = getVariableSolverData(fg, :b, :parametric) +@test isapprox(vnd.val[1], [0.01, -0.02, 0.03, -0.01, 0.02, -0.03], atol=1e-3) + + +## Test Case 3 + +df = CSV.read(@__DIR__() * "/testdata/IMUCase3.csv", DataFrame) + +σ_a = 0.037/60*sqrt(100) # noise density m/s²/√Hz - 0.037 m/s/√hr + +σ_ω = 0.15*pi*60/180/3600*sqrt(100) # noise density rad/√Hz - 0.15 deg/√hr +Σy = diagm([ones(3)*σ_a^2; ones(3)*σ_ω^2]) + +a_b = SA[0.,0,0] +ω_b = SA[0.,0,0] + +accels = map(SVector, zip(df.nax, df.nay, df.naz)) +gyros = map(SVector, zip(df.nwx, df.nwy, df.nwz)) + +# accels = map(SVector, zip(df.ax, df.ay, df.az)) +# gyros = map(SVector, zip(df.wx, df.wy, df.wz)) + +timestamps = df.time + + +pidx = range(1; step=100, stop=length(timestamps)) +factors = map(zip(pidx[1:end-1], pidx[2:end])) do (fr,to) + r = range(fr,to-1) + RoME.IMUDeltaFactor( + SVector{3,Float64}.(accels[r]), + SVector{3,Float64}.(gyros[r]), + ones(length(r))*Ts, + Σy, + a_b, + ω_b + ) +end + +times = timestamps[pidx] + +fg = initfg() +fg.solverParams.graphinit = false + +foreach(enumerate(Nanosecond.(times * 10^9))) do (i,nanosecondtime) + addVariable!(fg, Symbol("x",i-1), Pose3; nanosecondtime) + addVariable!(fg, Symbol("v",i-1), Position3; nanosecondtime) +end + +addFactor!(fg, [:x0], PriorPose3(MvNormal([1.0, 1, 1, 0, 0, 0], diagm(ones(6)*1e-3^2)))) +addFactor!(fg, [sortDFG(ls(fg, r"^x"))[end]], PriorPose3(MvNormal([1.0, 1, 1.0, 0, 0, 0], diagm(ones(6)*1e-3^2)))) + +for l in ls(fg, r"v\d")[1:1] + addFactor!(fg, [l], PriorPoint3(MvNormal([0.0, 0, 0], diagm(ones(3)*1e-3)))) +end + +# Variable for bias +addVariable!(fg, :b, Position{6}) + +for (i,fac) in enumerate(factors) + frx = Symbol("x",i-1) + frv = Symbol("v",i-1) + tox = Symbol("x",i) + tov = Symbol("v",i) + if exists(fg, :b) + addFactor!(fg, [frx,frv, tox, tov, :b], fac) + else + addFactor!(fg, [frx,frv, tox, tov], fac) + end +end + + +debug = [:Iteration, :Change, " | ", :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :damping_term, "\n", :Stop] +debug = [:Iteration, :Cost, " | ", :Stepsize," | ", :GradientNorm," | ", :last_step_successful, "\n", :Stop] +stopping_criterion=StopAfterIteration(1000) | StopWhenGradientNormLess(1e-12) | StopWhenStepsizeLess(1e-12) + +@time IIF.solveGraphParametric!(fg; stopping_criterion, debug, is_sparse=false, damping_term_min=1e-12, expect_zero_residual=false); + +vnd = getVariableSolverData(fg, :b, :parametric) + +@test isapprox(vnd.val[1], [0.01, -0.02, 0.03, -0.01, 0.02, -0.03], atol=1e-3) diff --git a/test/inertial/testdata/IMUCase1.csv b/test/inertial/testdata/IMUCase1.csv new file mode 100644 index 00000000..32268bd8 --- /dev/null +++ b/test/inertial/testdata/IMUCase1.csv @@ -0,0 +1,902 @@ +time,ax,ay,az,wx,wy,wz,nax,nay,naz,nwx,nwy,nwz +0.0,0.0,0.0,9.81,0.0,0.0,0.0,0.00840189240452825,-0.020972821493574555,9.846812691210737,-0.00978398883422844,0.021264214870045033,-0.03025434638423601 +0.01,0.0,0.0,9.81,0.0,0.0,0.0,0.012072659210545286,-0.020530105777355152,9.833699186871353,-0.011975785572730251,0.019933633954711247,-0.0261463954949685 +0.02,0.0,0.0,9.81,0.0,0.0,0.0,0.015542990542982056,-0.016543301941835196,9.851771936347921,-0.011164919449517117,0.02062126667583984,-0.028357139004947702 +0.03,0.0,0.0,9.81,0.0,0.0,0.0,0.012016978357973052,-0.02227815372680272,9.835960934885698,-0.0070830438386072355,0.01906229178180952,-0.030339738537669577 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