radio frequency alliance unmanned vehicle systems … · · 2011-10-18unmanned vehicle systems...

1

Radio Frequency Alliance

Unmanned Vehicle Systems Conference

Hyatt Regency, Indianapolis, Indiana

Remotely Piloted Aircraft

Dr. Mark T. Maybury

Chief Scientist

United States Air Force

Headquarters U.S. Air Force 27 September 2011

Public Released 04/21/11 (SAF PA 2011-232)

Future Air Force Science and Technology

Approved for public release, Distribution unlimited

RPA Groups by Payload and Range

2

10,000

1,000

100

10

1

1 10 100 1,000 10,000

Ma

x P

aylo

ad

(lb

s)

Max Radius (nm)

Group 5

Group 2

Group 1

Tiger Shark

RQ-7 Shadow

Scan Eagle

Reaper

Wasp III BATMAV

MQ-9 Reaper

MQ-1 Predator

RQ-4 Global Hawk

RQ -11 Raven

Group 3

Group 4 RQ-170

Sentinel

Approved for public release, Distribution unlimited 3

Usage Growth


Manning Growth

300 per CAP

168 per CAP

Our #1 manning problem in the Air Force

is manning our unmanned platforms

>70% of exploiters and maintainers


Need Human Centered

Ground Station Design

Excessive Inputs

Multiple Displays

Multiple Input

Devices

Poor Ergonomics

Visual Overload

Limited Task

Awareness

Uncomfortable

Small

Workspace

Multilayered

Menus

No graceful

degradation


Collateral Damage

RPAs enhance civilian protection

Highly precise, multisensor ISR improves target ID

Persistent, wide-area surveillance improves

Situation awareness

Acquisition/maintenance of positive ID

Tactical patience

Increased connectivity more “eyes on target” and remote

expertise/oversight

Precision strike/low collateral damage (LCD) munitions

Scorpion Low Collateral Damage/

Directed Lethality

“…we will not win based on the number of Taliban we kill, but

instead on our ability to separate insurgents from the center

of gravity - the people….” General David Petraeus


How will RPAs Change?

Today Tomorrow

Manpower Intensive Autonomous (pilot, sense, exploit)

Manually exploited full motion

video (FMV)

Wide Area Airborne Surveillance (WAAS), on board PED,

real time cross cueing

Human “in the loop” Human “on the loop”

Low Situational Awareness (SA) Super SA (fused sensors, health monitoring, …)

Manual Airspace Management Autonomous Airspace management and deconfliction

(e.g., onboard sense and avoid)

Individual platforms Multi-platform collaboration, manned/ unmanned

Collateral damage/fratricide

manually managed

Near zero collateral damage/fratricide

Continuous communications Intermittent, autonomous communications

Uncontested battlespace Contested (kinetic air/ground, EW, cyber) driving stealth,

defenses, secure comms, …

Limited missions (ISR, strike) Multi-mission capable (EW, counterair missile trucks,

refuel, ...) via modular platforms, payloads, comms, and

operator interfaces


Technology Horizons Priority Technology Areas

Autonomous systems

Autonomous reasoning and learning

Resilient autonomy

Complex adaptive systems

V&V for complex adaptive control

Collaborative/cooperative control

Autonomous mission planning

Cold-atom INS

Chip-scale atomic clocks

Ad hoc networks

Polymorphic networks

Agile networks

Laser communications

Frequency-agile RF systems

8 www.af.mil/shared/media/document/AFD-100727-053.pdf

Spectral mutability

Dynamic spectrum access

Quantum key distribution

Multi-scale simulation technologies

Coupled multi-physics simulations

Embedded diagnostics

Decision support tools

Automated software generation

Sensor-based processing

Behavior prediction and anticipation

Cognitive modeling

Cognitive performance augmentation

Human-machine interfaces

RPA OR RPA RELATED IN RED


Advancing RPA Roles and Capabilities

Beyond traditional surveillance and

kinetic strike roles

Humanitarian relief

Homeland security

Civilian employment

Advancing vectors

Endurance

ISR – coverage, accuracy,

diversity

On board processing

Autonomy

Distributed/Cooperative

Survivable – Stealth, EW

In-flight automated refueling

Directed energy (laser and HPM)


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


New Multi-Spot EO/IR Sensors for RPAs

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)


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


RPA Automated Aerial Refueling (AAR)

Aerial refueling of RPA 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 RPA 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 RPA AAR Algorithms

August 2006 initial flight tests of AFRL-developed

control algorithms for automated aerial refueling

KC-135 with Learjet-surrogate RPA 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


Increased Autonomy in RPA Missions

Autonomous mission optimization under

dynamic circumstances is a key capability

Must address RPA platform degradation as

well as changes in operating environment

Operator only declares mission intent and

constraints; RPA finds best execution path

Vigilent Spirit is current implementation


Distributed/Cooperative Control of RPAs

Optimized scalable solution methods

for multiple heterogeneous RPAs

Allows multiple RPAs 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


Distributed/Cooperative Control of RPAs

Task coupling of multiple RPAs is key in

complex environments; e.g. urban areas

Must include variable autonomy to allow

flexible operator interaction with RPAs

Allow dynamic task re-assignment while

reducing overall operator workload

Demonstrated in Talisman Saber 2009


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


Integration of RPA 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 Airspace National 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


RPA Autonomous Collision Avoidance

and Terminal Airspace Operations

Must address all aspects of RPA situational

awareness and control

Airspace deconfliction, air-ground collision

avoidance, terminal area operations

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

“remotely-piloted” becomes “unmanned”

Surface avoidance (vehicles, obstructions)

U-2 70K

60K

Global Hawk

Heron 1

Predator A

50K

40K

30K

20K

10K

Alt

itu

de

10 20

30 Endurance (hours)

Hermes, Aerostar,

Eagle Eye, Fire

Scout, Hunter

Heron 2

Predator B


“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


Trust in Autonomy:

Verification & Validation of RPA 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 a

major cost and schedule driver

High level of autonomy in RPAs

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 loss link

and latencies exacerbate

Traditional methods based on

requirements traceability fail

Extremely challenging problem;

must overcome for RPA “trust”

Requires entirely new approach

Graceful degradation, “safeing”


“Formal Methods” vs “Run-Time Method”

for V&V of RPA 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


Energy Horizons

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Vision: Assured energy advantage across

air, space, cyberspace and infrastructure

Reduce demand, increase supply, change

culture … increased resiliency

AFRL small engine laboratory (e.g., MQ-1B

Predator conversion to lower octane/direct

injection)

Laser power beaming to RPA

Bio-inspired (e.g., formation flying, energy

harvesting, perching)

Rotax 914

http://www.economist.com/node/17951584

Energy

Horizons USAF Energy

S&T Strategy


Batteries & Liquid Hydrocarbon Fuel Cells

to Power Small RPAs

Small RPAs 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 RPA


MAVs: New Aerodynamic Regimes and

Microelectromechanical Components

Micro Air Vehicles open up new

opportunities for close-in sensing in

urban areas

Low-speed, high-maneuverability, and

hovering not suited even to small RPAs

Size and speed regime creates low-Re

aerodynamic effects; fixed-wing RPAs

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


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


AMASE: Air Force Research Laboratory’s

AVTAS Multi-Agent Simulation Environment

Desktop simulation environment developed

at AFRL for RPA cooperative control studies

Used within AFRL to develop and optimize

multiple-RPA 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


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 RPAs 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

RPAs flown in Talisman Saber 2009

AMASE modeling details are documented and

publicly available in AIAA-2009-6139

Comparison of two cooperative

RPA control systems

93% areas covered

94 min. mission time

30% RPA energy used

100% areas covered

57 min. mission time

15% RPA energy used


Distributed Virtual RPA C2

Lesson: DCGS enables dynamic

operator (re)allocation for ISR tasks

In contrast, RPA ground stations lack

usability and tied to individual

platforms

Standard controls and interfaces

essential to pilot/platform

Desiderata: (Virtually) Decouple

sensors, platforms, and operators to

enable dynamic (re)llocation

31

Military Controlled Airspace

Ground

Forces

Controlled

Airspace ”Reference Grid”

“ROZ”


Concluding Remarks

We are still at the very early stages of

RPA evolution

Developments over next decade will

span from large RPAs to MAVs as key

technologies and missions evolve:

Advanced platforms and sensors

Operations in non-permissive areas

Automated aerial refueling

Coordinated control of multiple RPAs

RPA integration across airspace

V&V to provide trust in autonomy

Creative approaches and technology

advances will be needed to exploit the

full potential that RPAs can offer

radio frequency alliance unmanned vehicle systems … · · 2011-10-18unmanned vehicle systems...

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