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Map.jl
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default(size = 0.6 .* [800, 600])
default(palette = :tol_bright)
default(dpi = 300)
default(lw = 2)
default(margin = 1mm)
FontSize = 12
default(xtickfontsize = FontSize)
default(ytickfontsize = FontSize)
default(xguidefontsize = FontSize)
default(yguidefontsize = FontSize)
default(legendfontsize = FontSize)
default(titlefontsize = FontSize)
rng = MersenneTwister(1234)
function path(θ, p = 1, ArrOut = false)
if p == 1
nv = size(pv1, 1)
v = pv1
elseif p == 2
nv = size(pv2, 1)
v = pv2
else
error("invalid path choice at path function!")
end
ns = nv - 1
d = zeros(ns) #distances
for i = 1:ns
d[i] = EuclideanDistance(v[i, :], v[i+1, :])
end
td = sum(d)
Dθ = d ./ td .* Mp
s = 1
thisSegBound = 0
for i = 1:ns
thisSegBound = sum(Dθ[1:i]) #how far this segment goes
if θ <= thisSegBound
s = i
break
end
end
if s != 1 #not first segment, adjust bounds and theta
prevSegBound = sum(Dθ[1:(s-1)])
θ -= prevSegBound
thisSegBound -= prevSegBound
end
x = v[s, 1] + (v[s+1, 1] - v[s, 1]) * θ / thisSegBound
y = v[s, 2] + (v[s+1, 2] - v[s, 2]) * θ / thisSegBound
if θ > Mp
x = v[end, 1]
y = v[end, 2]
end
if ArrOut
return [x, y]
end
return x, y
end
function EuclideanDistance(x1, x2)
sqrt((x1[1] - x2[1])^2 + (x1[2] - x2[2])^2)
end
function uav_dynamics(x, y, vx, vy, dt, rem_power = Inf, vmax = Inf, m = 1.0)
vx > vmax ? vmax : vx
vy > vmax ? vmax : vy
vx < -vmax ? -vmax : vx
vy < -vmax ? -vmax : vy
x = x + vx * dt
y = y + vy * dt
rem_power = rem_power - vx^2 * m * dt - vy^2 * m * dt - m * alpha * dt
return x, y, rem_power
end
function simDeterministicUniform(Er = 8000)
clearconsole()
UASPos = [800, 450]
LPos = [400, 550]
ts = 0
PNRStat = false
N = 100
p = 2
dt = 1
PrevPNR = [0.0, 0.0]
μ = 80
Σ = 40
Ns = 5
β = 0.1
γ = 1.0
UASPosVec = zeros(N, 2)
anim = @animate for i = 1:N
UASPosVec[i, :] = UASPos
#TimeSamples = ts:120
TimeSamples = SampleTime(μ, Σ, N, ts)
TimeSamples = TimeSamples[:]
PosSamples = DriverPosFunction(TimeSamples)
elites = rankSampleMean(TimeSamples, UASPos, Ns, p)
elite = rankSampleMean(TimeSamples, UASPos, 1, p)
μn = sum(TimeSamples[elites]) / Ns
μ = γ * μn + (1 - γ) * μ
Σ =
β * (sum((TimeSamples[elites] .- μ) .^ 2) ./ Ns + 1) + (1 - β) * Σ
Σ = min(Σ, 100)
OptTimeSample = TimeSamples[elite]
v, t = DeterministicUniformMPC(
UASPos,
LPos,
OptTimeSample,
Er,
ts,
PrevPNR,
PNRStat,
p,
)
pp = plot()
pp = plot!(UASPosVec[1:i, 1], UASPosVec[1:i, 2], legend = false)
pp = drawConvexHull(TimeSamples, [1, 2], :green)
pp = drawConvexHull(TimeSamples[elites], [1, 2], :red)
pp = plotPlan!(UASPos, LPos, v, t, TimeSamples)
pp = scatter!(
path(DriverPosFunction(ts), p),
markersize = 6.0,
label = "",
markercolor = :green,
)
pp = plot!(tickfont = Plots.font("serif", pointsize = round(12.0)))
ts = ts + dt
PrevPNR = v[:, 1] .* t[1] .+ UASPos
Ed =
m[1] * v[1, 1]^2 * t[1] +
m[1] * v[1, 2]^2 * t[2] +
m[2] * v[1, 3]^2 * t[3] +
m[1] * v[2, 1]^2 * t[1] +
m[1] * v[2, 2]^2 * t[2] +
m[2] * v[2, 3]^2 * t[3] +
m[1] * alpha * t[1] +
m[1] * alpha * t[2] +
m[2] * alpha * t[3]
x, y, Er = uav_dynamics(
UASPos[1],
UASPos[2],
v[1, 1],
v[2, 1],
dt,
Er,
vmax,
PNRStat ? m[2] : m[1],
)
UASPos = [x, y]
@show t, i, Σ, μ, Er, Ed
if p == 2
pv = pv2
else
pv = pv1
end
if t[1] <= 1.0 ||
EuclideanDistance(path(DriverPosFunction(ts), p, true), pv[2, :]) <= 10
break
end
end
# proceed with rendezvous
gif(anim, "RDV_Anim.gif", fps = 15)
end
function simIndependentDistributions(Er = 8000)
clearconsole()
UASPos = [800, 450]
LPos = [400, 550]
ts = 0
PNRStat = false
N = 100
p = [1, 2]
ptgt = 2
dt = 1
PrevPNR = [0.0, 0.0]
μ = 80 * ones(2)
Σ = 40 * ones(2)
Ns = 5
β = 1.0
γ = 1.0
UASPosVec = zeros(N, 2)
OptTimeSample = zeros(length(p))
anim = @animate for i = 1:N
UASPosVec[i, :] = UASPos
#TimeSamples = ts:120
TimeSamples = SampleTime(μ, Σ, N, ts)
PosSamples = DriverPosFunction(TimeSamples)
elites = rankMultiPath(TimeSamples, UASPos, Ns, p)
elite = rankMultiPath(TimeSamples, UASPos, 1, p)
for j = 1:length(p)
μn = sum(TimeSamples[elites[:, j], j]) / Ns
μ[j] = γ * μn + (1 - γ) * μ[j]
Σ[j] =
β * (
sum((TimeSamples[elites[:, j], j] .- μ[j]) .^ 2) ./ Ns + 1
) + (1 - β) * Σ[j]
Σ[j] = min(Σ[j], 100)
OptTimeSample[j] = TimeSamples[elite[j], j]
end
ptgt = argmin(OptTimeSample)
v, t = DeterministicUniformMPC(
UASPos,
LPos,
OptTimeSample[2],
Er,
ts,
PrevPNR,
PNRStat,
2,
)
#TODO: Fix plotting of convex hull
pp = plot()
pp = plot!(UASPosVec[1:i, 1], UASPosVec[1:i, 2], legend = false)
pp = drawConvexHull(TimeSamples, [1, 2], :green)
pp = drawConvexHull(TimeSamples[elites], [1, 2], :red)
pp = plotPlan!(UASPos, LPos, v, t, TimeSamples)
pp = scatter!(
path(DriverPosFunction(ts), ptgt),
markersize = 6.0,
label = "",
markercolor = :green,
)
pp = plot!(tickfont = Plots.font("serif", pointsize = round(12.0)))
ts = ts + dt
PrevPNR = v[:, 1] .* t[1] .+ UASPos
Ed =
m[1] * v[1, 1]^2 * t[1] +
m[1] * v[1, 2]^2 * t[2] +
m[2] * v[1, 3]^2 * t[3] +
m[1] * v[2, 1]^2 * t[1] +
m[1] * v[2, 2]^2 * t[2] +
m[2] * v[2, 3]^2 * t[3] +
m[1] * alpha * t[1] +
m[1] * alpha * t[2] +
m[2] * alpha * t[3]
x, y, Er = uav_dynamics(
UASPos[1],
UASPos[2],
v[1, 1],
v[2, 1],
dt,
Er,
vmax,
PNRStat ? m[2] : m[1],
)
UASPos = [x, y]
@show t, i, Σ, μ, Er, Ed
if ptgt == 2
pv = pv2
else
pv = pv1
end
if t[1] <= 1.0 ||
EuclideanDistance(
path(DriverPosFunction(ts), ptgt, true),
pv[2, :],
) <= 10
break
end
end
# proceed with rendezvous
gif(anim, "RDV_Anim.gif", fps = 15)
end