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Copyright© 2011 Boeing Unpublished Work.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