Stan Ferguson AIAA Applied Aero Technical Committee.
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Transcript of Stan Ferguson AIAA Applied Aero Technical Committee.
Stan Ferguson
AIAA Applied Aero Technical Committee
Low Reynolds Number Workshop for MAVS
• Ming Chang and Michael OL• Micro Air Vehicles (MAVs) are:
– Flight articles resembling natural flyers (birds, bats, insects) in size and functionality.
– Interest since at least the 1990s,– Scientific and engineering progress has been episodic
• Advances more from trial-and-error than first-principles science• Pacing items are aerosciences payloads/energy/materials.
• Objective:– To explore the state of the art and where we have been in both the sciences and
applications– To identify who is pursuing what research and examine research directions and
interest for academia, industry and government. – To draw connection between the sciences and the applications. – To determine business-case
Paradigm Shift RequiredVulture , Span ~ 400 ft, VSL = 36fps
Phantom Eye , Span ~ 150 ft
Nano Hummingbird, Span ~ 0.54 ft, VSL = 22fps
Factor of 1200 on Reynolds Number
3 gm Dragonfly with camera ~ 0.33 ft
Paradigm Shift
Baby ZoeyDec 31, 2013
(Adapted by Petricca, et.al., from Mueller)
Aero Characteristics vs. Reynolds Number(McMasters and Henderson, Boeing)
DARPA DefinitionMAV NAV
Size (max dim.) <15.24 cm <15cmWeight (GTOW) 100 g <20gOperational Range 1 to 10 kmEndurance (TOS) 60 minOperational Altitude <150mMax Flight Speed 15 m/secMission Payload 20gMaximum Cost $1500
Challenges / State of the Art
1979: McMasters and Henderson, NASA CP 2085 “ Low-speed Element Airfoil Systhesis”
2006: Pines and Bohorquez, “Challenges Facing Future Micro-Air-Vehicle Development”
2011: Petricca, Ohlchers, and Grinde, “Micro and Nano – Air Vehicles: State of the Art”
8
Current UAS Programs
ScanEagle Integrator
A160 Hummingbird
Unmanned Little Bird
S-100
However, No MAVs
Copyright© 2011 Boeing Unpublished Work. All Rights Reserved--
Technologies• Mission Planning
• Surveillance and reconnaissance Coastal patrol, terrain mapping & surveying, anti-piracy, and port security
• Networked system – Integrated command and control – Scan Eagle, Unmanned LB and AWS systems– iPhone app pilots a remote UAV
• Plug and Play Sensors - Integrator• Autonomous systems - swarm technology –Integrator is completely
autonomous• Hydrogen propulsion system – Phantom Eye• Laminar flow – 787 / Phantom Eye• Shape memory materials – control system 787 /737• Conformal Solar Cell / Hydrogen fuel cell – Vulture• FAR Qualified - S100, Scan Eagle is allow is operate in commercial airspace
Autonomous Collaborative Systems-- The Challenge
John Vian, October 2013, CPStestbeds.ppt | 10
Remote control for simple tasks in simple
environment
Completes complex missions, adapts to changes ,and maximizes value
Plans and executes tasks to complete an operator specified
mission
Examples from today’s “simple” systems warn
of challenges ahead...
Automating coupled systems without
degrading safety, mission assurance, and security
is very difficult.
Autonomous cooperative systems can reduce operational costs and improve performance. However, development can difficult and risky.
http://www.nist.gov/el/isd/ks/autonomy_levels.cfm#
Accommodating increasing system complexity is very
difficult.
http://www.ntsb.gov/investigations
• Automated tasking & sequencing
• Cooperative control algorithms
• Health-adaptive architectures
• Automated & adaptive mission management
• Automated asset assignment• Multi-vehicle trajectory
planning• Automated de-confliction &
collision avoidance• Safety & emergency
behaviors• Automated fleet operations
& sustainment actions• Carefree human control and
interaction• V&V by design• …
Challenge 1: Hybrid Systems Health-adaptive Framework and Control Theory
Core Autonomy TechnologyApplications
technology reuse to reduce
development time
& cost NextG
enCom
mercial
Defense U
ASApplications
Civilian UAS
Applications
Factory Automated
Assembly
He
alth
-Ad
ap
tive
Au
ton
om
ou
s M
ulti-v
eh
icle
Sy
ste
ms
Tasks andResources
Task/ResourceController
Hea
lth C
ondi
tion
& Sy
stem
Cap
abilit
ies
Mission Plan andTrajectories
Mission Planner andTrajectory Generation
Vehicles
Control Allocationand Stabilization
Subsystems
Control andFault Adaptation
Goal -orientedCommands
Common Technology Supports Many Multi-vehicle Autonomous System Applications
44 Localization Cameras
Spectators Stages
Command & Control
Hardware Integration Station
Vehicles in Autonomous
Flight
Factory Mobile Robots
Health-adaptive Architecture
John Vian, October 2013, CPStestbeds.ppt | 11