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AIAA Infotech@Aerospace 2010

Exploiting Unmanned Aircraft Systems

Dr. Werner J.A. Dahm

USAF Chief Scientist

Air Force Pentagon

Headquarters U.S. Air Force 21 April 2010

Their Role in Future Military Operations

and the Emergent Technologies that

will Shape Their Development

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Current Unmanned Aircraft Systems of the U.S. Air Force and DoD

U.S. Army

MQ-1C WarriorRQ-7 Shadow

RQ-11 Raven

Wasp III BATMAV

U.S. Navy / Marines

RQ-2 Pioneer

RQ-11 Raven Scan Eagle

RQ-8 Fire Scout

U.S. Air ForceRQ-4 Global Hawk

MQ-1 PredatorMQ-9 Reaper

RQ-11 Raven

Wasp III BATMAV

RQ-170

Sentinel

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Rapid Growth in UAS Use by USAF

USAF Need for RPA Pilots, Operators, and Ground Crews is Growing Quickly

2004 2009 2011

RQ-4 Global Hawk MQ-1 Predator MQ-9 Reaper

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Emerging Roles and New Concepts forLarge and Medium Size UAVs

UAS moving beyond traditional

surveillance and kinetic strike roles

Longer-endurance missions require

high-efficiency engine technologies

In-flight automated refueling will be

key for expanding UAS capabilities

May include ISR functions beyond

traditional electro-optic surveillance

LO may allow ops in contested or

denied (non-permissive) areas

Electronic warfare (EW) by stand-in

jamming is a possible future role

Wide-area airborne surveillance

(WAAS) is increasingly important

Directed energy strike capability is

likely to grow (laser and HPM)

Civil uses include border patrol and

interdiction, and humanitarian relief

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Ultra-Long Endurance Unmanned Aircraft

New unmanned aircraft systems (VULTURE)

and airships (ISIS) can remain aloft for years

Delicate lightweight structures can survive

low-altitude winds if launch can be chosen

Enabled by solar cells powering lightweight

batteries or regenerative fuel cell systems

Large airships containing football field size

radars give extreme resolution/persistence

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New Multi-Spot EO/IR Sensors for UAVs

Multi-spot EO/IR cameras allow individually

steered low frame rate spots; augment FMV

Gorgon Stare now; ARGUS-IS will allow 65

spots using a 1.8 giga-pixel sensor at 15 Hz

Individually controllable spot coverage goes

directly to ROVER terminals on ground

Autonomous Real-Time Ground Ubiquitous

Surveillance - Imaging System (ARGUS-IS)

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New LIDAR Systems Allow Large-Area Three-Dimensional Urban Mapping

Light Detection and Ranging (LIDAR) allows

3D sensing with light-wavelength resolution

Allows detailed mapping of complex urban

areas from unmanned airborne systems

Merge with EO/IR images to give enhanced

spatial cognition and situational awareness

Low-collateral-damage strikes in urban

areas via target-quality 3D pixel coordinates

UAS Automated Aerial Refueling (AAR)

Aerial refueling of UAVs from USAF tanker fleet is

essential for increasing range and endurance

Requires location sensing and relative navigation

to approach, hold, and move into fueling position

Precision GPS can be employed to obtain needed

positional information

Once UAV has autonomously flown into contact

position, boom operator engages as normal

Key issues include position-keeping with possible

GPS obscuration by tanker and gust/wake stability

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Flight Testing of UAS AAR Algorithms

August 2006 initial flight tests of AFRL-developed

control algorithms for automated aerial refueling

KC-135 with Learjet-surrogate UAS platform gave

first “hands-off” approach to contact position

Subsequent positions and pathways flight test

and four-ship CONOPS simulations successful

120 mins continuous “hands-off” station keeping

in contact position; approach from ½-mile away

12 hrs of “hands-off” formation flight with tanker

including autonomous position-holding in turns

Position-holding matched human-piloted flight

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Increased Autonomy in UAS Missions

Autonomous mission optimization under

dynamic circumstances is a key capability

Must address UAV platform degradation as

well as changes in operating environment

Operator only declares mission intent and

constraints; UAV finds best execution path

Vigilent Spirit is current implementation

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Distributed/Cooperative Control of UAVs

Optimized scalable solution methods

for multiple heterogeneous UAVs

Allows multiple UAVs to act as single

coordinated unit to meet mission need

Scalability of methods is essential to

allow future application to larger sets

np-hard problem; exponential growth

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Distributed/Cooperative Control of UAVs

Task coupling of multiple UAVs is key in

complex environments; e.g. urban areas

Must include variable autonomy to allow

flexible operator interaction with UAVs

Allow dynamic task re-assignment while

reducing overall operator workload

Demonstrated in Talisman Saber 2009

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Growing DoD Need to Improve Process for Integrating UAS in National Airspace

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Growing DoD Need to Improve Process for Integrating UAS in National Airspace

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Integration of UAS Operations in National,

International, and Military Airspace

Authority:

Federal Aviation Authority (FAA)

Separation:

Cooperative: TCAS / ADS-B

Non-Cooperative: Visual

Airfields:

Friendly and well known

International AirspaceNational Airspace Military Airspace

Collision

Avoidance

Conflict

Avoidance

Authority:

Int’l. Civil Aviation Org. (ICAO)

Separation:

Cooperative: TCAS

Non-Cooperative: Visual

Airfields:

Limited access, not well known

Authority:

Department of Defense (DoD)

Separation:

Cooperative: IFF

Non-Cooperative: Radar, Visual

Airfields:

Limited, austere, security

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UAS Autonomous Collision Avoidance

and Terminal Airspace Operations

Must address all aspects of UAV situational

awareness and control

Airspace deconfliction, air-ground collision

avoidance, terminal area operations

Must be immune to UAS “lost-link” cases;

“remotely-piloted” becomes “unmanned”

Surface avoidance (vehicles, obstructions)

U-270K

60K

Global Hawk

Heron 1

Predator A

50K

40K

30K

20K

10K

Alt

itu

de

1020

30Endurance (hours)

Hermes, Aerostar,

Eagle Eye, Fire

Scout, Hunter

Heron 2

Predator B

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“Sense-and-Avoid” (SAA) System for

In-Flight Collision Avoidance

Sense-and-Avoid was Global Hawk ATD

for in-flight collision avoidance system

Flight on surrogate aircraft began 2006

Autonomous detection and avoidance of

cooperative & non-cooperative intruders

Jointly Optimal Collision Avoidance

(JOCA) was transition program in 2009

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Developing Increased Trust in Autonomy:

Verification & Validation of UAS Control

Flight Control Requirements

Control Design

Control Analysis

Software Requirements

Software Design

Software Implementation

Software Test & Integration

System Requirements

System Architecture Design

System Verification & Validation

System Architecture Analysis

Systems and software V&V is a

major cost and schedule driver

High level of autonomy in UAVs

will require new V&V methods

IVHM for mission survivability

Complex adaptive systems with

autonomous reconfigurability

Approach infinite-state system

even for moderate autonomy

Data/communication drop-outs

and latencies make even harder

Traditional methods based on

requirements traceability fail

Extremely challenging problem;

must overcome for UAS “trust”

Requires entirely new approach

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“Formal Methods” vs “Run-Time Method”

for V&V of UAS Control Systems

Formal methods for finite-state systems

based on abstraction and model-based

checking do not extend to such systems

Probabilistic or statistical tests do not

provide the needed levels of assurance;

set of possible inputs is far too large

Classical problem of “proving that failure

will not occur” is the central challenge

Run-time approach circumvents usual

limitation by inserting monitor/checker

and simpler verifiable back-up controller

Monitor system state during run-time and

check against acceptable limits

Switch to simpler back-up controller if

state exceeds limits

Simple back-up controller is verifiable by

traditional finite-state methods

Run-time

V&V system

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Batteries & Liquid Hydrocarbon Fuel Cells

Will Be Needed to Power Small UAVs

Small UAVs need suitable power source

for propulsion and on-board systems

Desired endurance times (> 8 hrs) cause

battery weight to exceed lift capacity; IC

engine fuel efficiencies are too low

Fuel cells give lightweight power system

but must operate on logistical LHC fuel

JP kerosene fuels ideal, liquid propane is

usable; need on-board fuel processor

Solid-oxide fuel cells are best to date;

current record held by U. Michigan team

> 9 hrs aloft with propane in small UAV

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MAVs: New Aerodynamic Regimes and

Microelectromechanical Components

Micro UAVs open up new opportunities

for close-in sensing in urban areas

Low-speed, high-maneuverability, and

hovering not suited even to small UAVs

Size and speed regime creates low-Re

aerodynamic effects; fixed-wing UAVs

become impractical as size decreases

Rotary-wing and biomimetic flapping-

wing configurations are best at this size

Requires lightweight flexible structures

and unsteady aero-structural coupling

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Low Reynolds Number Flow Associated

with Flapping-Wing Micro Air Vehicles

Unsteady aerodynamics w/ strong coupling

to flexible structures is poorly understood

AFRL water tunnel with large pitch-plunge

mechanism allows groundbreaking studies

Advanced diagnostics (SPIV) combined with

CFD are giving insights on effective designs

MAV aerodynamics, structures, and control

are accessible to university-scale studies

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AMASE: Air Force Research Laboratory’s

AVTAS Multi-Agent Simulation Environment

Desktop simulation environment developed

at AFRL for UAV cooperative control studies

Used within AFRL to develop and optimize

multiple-UAV engagement approaches

Public-released by AFRL to universities; no

license restrictions and no acquisition cost

Self-contained simulation environment that

accelerates iterative development/analysis

AMASE User Interface

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AMASE Can Be Used to Develop/Assess

New Collaborative Control Algorithms

Example shows comparison of control laws for

mission with multiple areas and no-enter zones

Heterogeneous UAVs make intuitive approach

too complex; results show performance differs

Allows effectiveness of control algorithms to

be quantitatively assessed and compared

Enabled maturation of process algebra laws for

UAVs flown in Talisman Saber 2009

AMASE modeling details are documented and

publicly available in AIAA-2009-6139

Comparison of two cooperative

UAS control systems

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Concluding Remarks

We are still at the very early stages of

UAS evolution, roughly where aircraft

were after WWI; much is changing

Developments over next decade will

span from large UAVs to MAVs as key

technologies and missions evolve:

Advanced platforms and sensors

Operations in non-permissive areas

Automated aerial refueling

Coordinated control of multiple UAVs

UAS integration across airspace

V&V to provide trust in autonomy

Creative approaches and technology

advances will be needed to exploit the

full potential that UAVs can offer