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The aim of the thesis is to inspect and derive a model for an autonomous VTOL that could help Mountain Rescue in finding the position of buried person under avalanche. The first part of the thesis will inspect the state of the art in buried searching, ARTVA transmitter and searching algorithms. Also we will show some of the requirements and technical specifications for a searching drone. In the second chapter we will expose the problem of searching the position of a transmitting source in near-field with ferromagnetic antennas. The chapter will be closed with a design for a digital ARTVA receiver. In the third chapter, a new kind of searching algorithm will be defined, including routines of obstacle-avoidance and altitude-keeping. In the fourth chapter, a model of an hexa-copter and its stabilization controls are derived and simulated in MATLAB/Simulink. The loop is closed on some of the searching algorithm defined in the previous chapter. Results of searching routine are shown and critically examined. The last chapter will take into account all the results to derive some conclusions about the stated problem, with some suggestions for further improvements.
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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
Recommended