Autonomous VTOL for Avalanche Buried Searching - AVIONICS (slides)
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Transcript of Autonomous VTOL for Avalanche Buried Searching - AVIONICS (slides)
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Autonomous VTOL for Avalanche Buried Searching
AvionicsMatteo Ragni
Ingegneria Meccatronica Robotica
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Introduction to Mountain Rescue
Drone Avionics
Design of a Digital ARTVA
Simulations and Conclusions
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Introduction to Mountain Rescue
Drone Avionics
Design of a Digital ARTVA
Simulations and Conclusions
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Mountain Rescue Intervention
I Call from witnesses or hikers indanger
I Helicopter missionI Evaluation of critical riskI Searching on avalanche surfaceI Searching for ARTVA signal presenceI Fine ARTVA searchingI Buried extraction
2. Starting Point
Buried5. Pinpointing a victim: ~2min
3. Searching for a signal
4. Signal found
1. Helicopter drops the rescue team
0 50 100 150
20
40
60
80
100
Time (min)
Cha
nces
ofsu
rviv
al(%
)
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
ARTVA Beacons Overview
I A1A Signal:
I amplitude modulateddigital signal
I one carrierfrequency: 457kHz
I frequency error±80Hz
I H–field peak at 10m
I ≥ 0.5 µA m−1
I ≤ 2.23 µA m−1Time
x
Inte
llige
nce
0
1
y
≥ 70ms ≥ 400ms
1000± 300ms
Triple
Antennas
Frequency shift
Anti–alias filter
A–D
Conversion
Digital FilterSignal
Detection
H–field
Estimation
Analog
Digital
TX MODE
RX MODE
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
H–Field in Transmission
Field Complexity
; ;
Simplified Equations for H–field
B(r, m) =µ0
4πr5
2x2 − y2 − z2 3xy 3xz
3xy 2y2 − x2 − z2 3yz
3xz 3yz 2z2 − x2 − y2
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Introduction to Mountain Rescue
Drone Avionics
Design of a Digital ARTVA
Simulations and Conclusions
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Perception–Action Map
Litterature overview...
Model
Hypothesis
Emulator
Grounding
Environment
Agent
I Subsumption and groundingI Emulation
... applied to our agent
Perception
Dynamics and control
Tracking Problem
Obstacle Avoidance
Altitude Keeping
Sourcesearching
Emulation
Radar detect
Explo-ration
routines
Action
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Dynamics, control and tracking
LQR Control
Li =mg6
x = f (x, u) 1s
u x
xfK −
−
u∗ e
Newton–Euler Equations
xg
yg
zgxb
yb
zb LiMi
π/3 x = [x, y, z, φ, θ, ψ, u, v, w, p, q, r]T
u = [Li : i = 1..6]
x = f (x, u)
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Obstacle Avoidance
ui
v(di)
v
di
obstacle
v = R(φ, ψ, θ)6∑
i=1v(di)
cos
((i− 1)
π
3
)− sin
((i− 1)
π
3
)0
I Advantages
I low computation neededI minor constraint on upper layersI fit QFD constraints
I Drawbacks
I non–optimal pathsI limited reliability
Speed function example:
v(di) = p3
(1
1 + e4(
p12 −di
)p2p3
− 1
)
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Altitude Keeping
Identification of the surface normal m −→ S.L.A.M. Problem
x
m
mt-1
mt
h
A
C B
mt =(A− B)× (B− C)|(A− B)× (B− C)|
Keep the VTOL at costant distance h along exstimated plane normal mt
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Exploring and Searching Signal Presence
Explore the surface, starting from point p0, to the point pn
p0
pn
Plane dire
ction
Receiver range
We need a strategy to understand if there is a signal
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Radar Detection Problem for Signal Presence
Signal Source
Z0Z1
Z
p(s|H1)p(s|H0)
Z0 Z1
s
p(s)p(s|H1)
p(s|H0)
← s→
PMPD
Z0 Z1
s
p(s)p(s|H1)
p(s|H0)
PCPF
Minimize the risk incurred due to erroneous decisions
min R = R(ci,j, PX) →Z0 = s ∈ Z : ∆(s) < η
Z1 = s ∈ Z : ∆(s) > η
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Pinpointing Signal Source
Searching the Maximum H–field
H∇H
|H| cos θ
|H| sin θ
θ
vPrevious
knowledge
ψ
|v|
cos θ
∇Hsin θ
|H|
Emulation of an H–field
And for multiple burials?
The stimated position is given by thesolution of the optimization problem:
min δ =(H−H(pt, m, x)
)2
(pT − x)2 ≤ rmax
and treated as a stochastic variable
p(p) =1N
N∑
k=1
γ(p− pk, h)V(h)
from p(p) we extract mean andcovariance!
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Introduction to Mountain Rescue
Drone Avionics
Design of a Digital ARTVA
Simulations and Conclusions
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Design of a Digital ARTVA
General Overview
Power supply
Tuned tank Filter stage Identification Filter stage
ADC
Triple antennas
x
y
z
Analogstage
Power supply
Analogstage
Analogstage
Digitalstage
Ferrite rod
Loop solenoid
Preamplifier
Amplifier
Identification
Tune
d Ta
nk
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Schematics – Antenna and PreAmplifier
103 104 105 106 107 108−150
−100
−50
0
50
Frequency (Hz)
Mag
nitu
de(d
B)
PreAmplifier Characteristic
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Schematics – Identification and Amplifier
100 101 102 103 104−150
−100
−50
0
Frequency (Hz)
Mag
nitu
de(d
B)
Amplifier Characteristic
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Introduction to Mountain Rescue
Drone Avionics
Design of a Digital ARTVA
Simulations and Conclusions
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Simulation Results (1)
0
5
10
15
20
−30
−25
−20
−15
−10
−5
0
5
0
5
10
x(m)
y(m)
z(m)
0 20 40 60 80 100 120 140−30
−20
−10
0
10
20
Time (s)
Posi
tion
(m)
x y z
0 20 40 60 80 100 120 140
0
1
2
3
Time (s)
Att
itud
e(r
ad)
φ θ ψ
0 20 40 60 80 100 120 140−1
0
1
2
3
Time (s)
Velo
city
(m/s
)
u v w
0 20 40 60 80 100 120 140
−4
−2
0
Time (s)
Ang
ular
rate
(rad
/s)
p q r
0 20 40 60 80 100 120 140
−1
−0.5
0
0.5
1
Time (s)
Lear
ned
orie
ntat
ion
cos(θ) cos(θ) real sin(θ) sin(θ) real
0 20 40 60 80 100 120 14010−6
10−5
10−4
10−3
Time (s)
Lear
ned
inte
nsit
y(A
/m)
|H| |H| real
Position found in 110s
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Simulation Results (2)
−30 −20 −10 0 10 20 30 40 50 60−60
−50
−40
−30
−20
−10
0
10
20
30
x(m)
y(m)
Drone positionTransmitter positionOptimization resultsLatest optimization resultsObstacle
0.00 0.05 0.10 0.15−60
−50
−40
−30
−20
−10
0
10
20
30
p(ptx,y|H)
−30 −20 −10 0 10 20 30 40 50 600.00
0.05
0.10
0.15
p(p
tx,x|H
)
Further improvements: weight the solutionswith respect to time!
x
y
0 50 100 1500
2
4
6
Time (s)
Dis
tanc
ed 0
(m)
0
50
100
150
0
2
4
6
Tim
e(s
)
Distance dπ/3 (m)
0
50
100
150
0
2
4
6
Time
(s)
Distance d 2π/3
(m)050100150
0
2
4
6
Time (s)
Dis
tanc
ed π
(m)
0
50
100
150
0
2
4
6
Tim
e(s
)
Distance d4π/3 (m)
0
50
100
150
0
2
4
6
Time
(s)
Distance d 5π/3
(m)
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Conclusions
ARTVA
I A review of the ARTVA protocol is strongly advisedI The ferrite antennas must be carefully modeledI Move from analog devices to software–defined–radio for better performance
Avionics
I Perception–Action map fits our problem requirementI A wiser emulator should be defined, with time related weightsI Performance can be improved by augmenting perception
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Questions?
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
State of the Art
Projects
I SHERPA: Universita di BolognaI Universita di TorinoI Project Alcedo Eidgenossische Technische Hochschule Zurich
Digital searching algorithms
I H–Field Lobe Following and pinpointingI Fast identification with SLAM and sum of Gaussian
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Maxwell Formulation
Application of potential vectors and recalibration map to Maxwell’s eq.
∇ · B = 0
∇× E = − ∂
∂tB
∇ · E =ρ
ε0
∇× B = µ0
(J + ε0
∂
∂tE)
∇2φ− 1
c2∂2φ
∂t2 = − ρ
ε0
∇2A− 1c2
∂2A∂t2 = −µ0J
B = ∇×A
E = −∇φ− ∂A∂t
A′ 7→ A +∇ψ
φ′ 7→ φ− ∂ψ
∂t
∇ ·A′ = − 1c2
∂2ψ′
∂t2
Application to our problem: integral formulation
φ(r, t) =1
4πε0
∫Ω
1|r− r′|ρ
(r′, t− |r− r′|
c
)dr
A(r, t) =µ0
4π
∫Ω
1|r− r′| J
(r′, t− |r− r′|
c
)dr
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Magnetic dipole problem
For a magnetic dipole problem: φ = 0!
Solution for boundary condition problem
xy
z
ϕ′
J
dr
r
κ = |r− r′|
r′
θψ A =
µ0m0
4πrsin(θ)
(1r
sin (ω0(t− r/c))−
+ω0
rcos (ω0(t− r/c))
)φ
Under the hypothesis: r′ r and r′ λ
B–Field solution
τ = t− rc
Br =µ0m0
2πr2 cos(θ)(
1r
cos(ω0τ)− ω0
csin(ω0τ)
)Br =
µ0m0
4πr3csin(θ)
((c2 −ω2
0r2) cos(ω0τ)−ω0rc sin(ω0τ))
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Simulating a Range Finder
√d2
i − u2
d i=|x
Ψi− x d|
ρ
hu
(xΨi − xd)
ui
ρ (maximum radius)
u = (xΨi − xd) · ui
h (maximum range)
Characteristic lobe
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Simulink Implementations (1)
Hexacopter Model
Parameters
+Fi =mg6
LQR Controller 1s
z attitude
+SearchingAlgorithm
ObstacleAvoiding
x
x Range Finder Model di
Ψ = [xi : i = 1..M]
[h, ρ]
RT(φ, θ, ψ)
vb =6∑
i=1v(di)ui × v
[p1, p2, p3]
Outline Introduction to Mountain Rescue Drone Avionics Design of a Digital ARTVA Simulations and Conclusions Q&A
Simulink Implementations (2)
x H sensor
Magnetic Dipole m
TX position pT
|H|
cos(θ)
sin(θ)
α1s + 1β1s2 + β2s + 1
Explo-ration
directionv
Emulation(H− H)2 = 0
Optimized pT
Optimized m
Parameters
x H (x, pT, m)
Magnetic Dipole m
TX position pT
|H|
×N (0, Σ) SNR
+ H