model-based virtual in-the-loop-test of autonomous systems: the falter case
DESCRIPTION
Presentation at the 2nd International Workshop on Model-driven Approaches for Simulation Engineering (held within the SCS/IEEE Symposium on Theory of Modeling and Simulation part of SpringSim 2012) Please see: http://www.sel.uniroma2.it/mod4sim12/ for further detailsTRANSCRIPT
The FALTER Case
Model-‐Based So,ware In-‐the-‐Loop-‐Test of Autonomous Systems
Andreas Bayha, Franziska Grüneis, Bernhard Schätzfor9ss gGmbH
Mod4Sim@TMS/DEVS, Orlando, 27.03.2012
FALTER Project
FALTER: Flugeinheit zur Autonomen Lage-‐ und Terrain-‐Erkundung Mission: Autonomous flight for in-‐situ indoor analysis (no GPS signal) PlaBorm: Quadrocopter with IF/US/IMU Autonomy: Online-‐replanning for collision avoidance
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Mission Management
FALTER
MissionData
ResultInformation
ExecuteMission
FALTER: HW-‐PlaHorm
HW-‐ConstrucJon: Modular PlaKorm Sensors: Incl. gyroscope, ultrasonic, Pme-‐of-‐flight camera, alPmeter Actuators: Motors, camera CommunicaPon: Mission data/goal informaPon, emergency-‐off Flight control: COTS-‐control unit for quadrocopter Mission control: Embedded-‐qualified GP control unit
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FlightCrtl
RoBoard
Ultra Sonic
Camera
Battery
Motors
CompassRC Reciever
Safety switch RS232
PWM
I!C
I!C
USB
BluetoothWLAN
PWM
PWM
Gyros
Accels
FALTER: So,ware VerificaJon
So,ware Architecture HW-‐abstracPon layer ApplicaPon layer: Mission funcPons Control: Measuring and Control ExecuPon: Handling of flight leg Planning: (Re-‐)Planning of mission path
VerificaJon Goals Reliability: Faults of plaBorms Robustness: SituaPons in environment
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Application Layer
Hardware & Abstraction Layer
FALTER-HAL
RoBoard-HAL
RoBoard
FlighCtrl-HAL
FlightCrtl
Planing
Control
Execution
FALTER Data
Environment Data
Command Sense
FALTER Project: IntegraJon Test
FALTER: Complicated and risky integraJon test Complex state space (incl. internal model of environment) Complex environment (incl. plaBorm faults, unexpected obstacles) Safety criPcal funcPonality (incl. man and material)
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Virtual IntegraJon: Simulated PlaKorm and Environment
Virtual Commissioning: Models for VerificaJon/ValidaJon Pla$orm model: HAL, hardware, electronics&mechanics of system
FALTER: Model of local parameters (e.g., posiCon, speed) Environment model: Physical environment of system
FALTER: Model of global parameters (e.g., walls, obstacles) Virtual Commissioning: ExecuCon of applicaCon on simulated plaKorm in simulated environment
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Environment
FALTER
Platform
Control
Execute
Planning
FALTER Model
Environment Model
Command& Sense
EnvironmentModel
Virtual FALTER
Platform Model
Control
Execute
Planning
FALTER Model
Environment Model
Command& Sense
UAV SimulaJon: State of the Art -‐-‐Tools
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UAV SimulaJon: Tools for Model ConstrucJon1. RC Simulators: SimulaCon of UAVs for RC training (e.g., FMS)
SiL-‐Usage: 6-‐DoF-‐Models, no environment and sensor models2. Physics simulators: SimulaCon mech./elec. processes (e.g. SimScape)
SiL-‐Usage: Solids/fluids models, no dyn. environment and sensor models
SimulaJon: Structure
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Structure: Modular Components• Environment model: Walls, obstacles• Sensor model: Ultrasonic, time-of-
flight, gyroscopes, accelerators • Actuator model: Flight mechanics,
power electronics• Platform model: Preprocessing, flight
control, API • Control software: Unmodified
software
Control So]ware
PlaBormModel
SensorModel
ActuatorModel
EnvironmentModel
SimulaJon: Actuator model
Actuator model: Handling of flight mechanics Physics: 6DoF-‐MoPon model Actuators: TranslaPon control commands via power electronics
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Walls
[]
Roboard
WallsPositionDCMFC ACCFC GYRO
LEDGASGierNickRoll
Flight Dynamics
GASYAWNICKROLLrad/s
F
M
6DoF (Euler Angles)
Fxyz
(N)
Mxyz
(N m)
Ve (m/s)
Xe (m)
(rad)
DCMbe
Vb (m/s)
(rad/s)
d /dt
Ab (m/s2)
BodyEuler Angles
FixedMass
Walls
[]
Roboard
WallsPositionDCMFC ACCFC GYRO
LEDGASGierNickRoll
Flight Dynamics
GASYAWNICKROLLrad/s
F
M
6DoF (Euler Angles)
Fxyz
(N)
Mxyz
(N m)
Ve (m/s)
Xe (m)
(rad)
DCMbe
Vb (m/s)
(rad/s)
d /dt
Ab (m/s2)
BodyEuler Angles
FixedMass
SimulaJon: Environment and Sensor Model
Sensor Modell: Distance/PosiJon Measurement Distance Measurement: PosiCon-‐dependent distance list
PosiCon detecCon: Provision of 6DoF-‐values
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y
z
v
e2
e1
Environment Model: Walls, Obstacles Surfaces: One-‐Vertex-‐Dual-‐Edges-‐Encoding of rectangles
Walls, Obstacles: CombinaCon of surfaces
SimulaJon: ImplementaJon
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Implementation: Matlab/Simulink• Simulation: Simulink Aerospace Toolbox, simulation components• Visualization: Simulink 3D Simulation (aka VR Toolbox)
• Software inclusion: S-function via API of Platform Model
SimulaJon: Fault Model
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EffecPve Signal Signal+Dri] Signal+Dri]+Noise
Fault Model: Support for generic classes of faults• Systemic faults, e.g., noise, drift• Sporadic faults, e.g., bit-flip, stuck-at
• Parametrized faults, e.g., fail time, noise strength
SimulaJon: ApplicaJon
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Intended Z-‐Speed/AlPtude
EffecPve Z-‐Speed/AlPtude
Assumed Speed/AlPtude
Application: In-the-Loop Test incl. Debugging by Simulation• Execution of software, simulation of platform and environment
Test Management
Test Management System: Scenarios Easily reproducable setups for in-‐the-‐loop tests Independent combinaPon of noise, dri], blackout, obstacles
ApplicaPon: Reliability (faults), robustness (obstacles)14
SimulaJon: ApplicaJon
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Virtual SiL Test
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at our site at www.fortiss.org
More InformaJon:
SimulaJon Framework for UAVs Standard architecture (Environment, sensors, pla$orm, actuators) Modular components (incl. ultrasonic, Cme-‐of-‐flight) Robustness/reliability test (incl. obstacles, sensor defects, Cming faults) Debugging support (incl. internal environment model)
➡ Efficient support of early and low-‐risk validaCon/verificaCon➡ LimitaCon due to degree of details (e.g., energy effects, surface properCes)