AIAA Infotech@Aerospace 2010
Exploiting Unmanned Aircraft Systems Their Role in Future Military Operations and the Emergent Technologies Technologies that will Shape Their Development Dr. Werner J.A. Dahm USAF Chief Scientist Air Force Pentagon Headquarters U.S. Air Force
21 April 2010
Current Unmanned Aircraft Systems of the U.S. Air Force and DoD U.S. Air Force
RQ-4 Global Hawk
MQ-1 Predator
MQ-9 Reaper
RQ-11 Raven Wasp III BATMAV RQ-170 Sentinel
U.S. Army RQ-7 Shadow
MQ-1C Warrior
U.S. Navy / Marines RQ-11 Raven
Scan Eagle
RQ-8 Fire Scout
RQ-11 Raven Wasp III BATMAV
RQ-2 Pioneer
Rapid Growth in UAS Use by USAF
USAF Need for RPA Pilots, Operators, and Ground Crews is Growing Quickly RQ-4 Global Hawk
2004
MQ-1 Predator
2009
MQ-9 Reaper
2011
Emerging Roles and New Concepts for Large 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
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 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)
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
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
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
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
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
Growing DoD Need to Improve Process for Integrating UAS in National Airspace
Growing DoD Need to Improve Process for Integrating UAS in National Airspace
Integration of UAS Operations in National, International, and Military Airspace National Airspace Authority : Federal Aviation Authority (FAA) Separation : Cooperative : TCAS / ADS-B Non-Cooperative : Visual Airfields : Friendly and well known
International Airspace Authority : Int’l. Civil Aviation Org. (ICAO)
Separation : Cooperative : TCAS Non-Cooperative : Visual Airfields : Limited access, not well known
Collision Avoidance
Military Airspace Authority : Department of Defense (DoD) Separation : Cooperative : IFF Non-Cooperative : Radar, Visual Airfields : Limited, austere, security
Conflict Avoidance
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-2
70K
Global Hawk
60K e d 50K u t i t 40K l A
Heron 2 Predator B
30K 20K 10K
Hermes, Aerostar, Eagle Eye, Fire Scout, Hunter
10
Endurance (hours)
20
30
Heron 1 Predator A
“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
Developing Increased Trust in Autonomy: Verification & Validation of UAS Control
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
System Requirements System Architecture Design System Architecture Analysis Flight Control Requirements Control Design Control Analysis Software Requirements Software Design Software Implementation Software Test & Integration System Verification & Validation
“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
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
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 flappingwing 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 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
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
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
