MASThesis_FutureOfMicroAerialVehicles

Running head: MICRO AIR VEHICLES: THE FUTURE OF UNMANNED ATMOSPHERIC AND SPACE FLIGHT 1
ASCI 691 Graduate Capstone
Micro Air Vehicles: The Future of Unmanned Atmospheric and Space Flight
Astrid Thundercliffe
Embry-Riddle Aeronautical University
ASCI 691 Graduate Capstone
Submitted to the Worldwide Campus
In Partial Fulfillment of the Requirements of the Degree of
Master of Aeronautical Science
2 March 2014

MICRO AIR VEHICLES: THE FUTURE OF UNMANNED ATMOSPHERIC AND SPACE FLIGHT 2
Abstract
The unmanned flight capabilities of the emerging class of micro air vehicle (MAV) will be
examined using existing operational data on traditional unmanned air vehicles (UAVs) as well as
experimental aerodynamics data for next generation low Reynolds number aircraft. The benefits
and limitations of MAV use for remote sensing and exploration of atmospheric and spaceflight
will be discussed. The mission and design requirements of MAVs for future terrestrial
surveillance and Mars exploration will be analyzed using present Department of Defense and
National Air and Space Administration (NASA) program initiatives. Human factors associated
with the command and control of MAVs will be explored, and recommendations for MAV
control systems will be made. The integration of unmanned aerial vehicles, including MAVs, in
the civil airspace will be discussed according to recent Federal Aviation Administration (FAA)
legislation. National and international space policy will be examined for concerns about MAV
use and exploration of Mars.
Keywords: micro air vehicle, unmanned air vehicle, low Reynolds number, remote
sensing, atmospheric flight, spaceflight, human factors, control systems, Federal Aviation
Administration, Department of Defense, National Air and Space Administration, civil airspace,
space policy

Proposal
The challenges of manned flight have dominated the aeronautical field for the majority of
the 20th century. The successful harnessing of manned atmospheric and spaceflight physics has
given rise to ever greater flight capabilities including the recent emergence of unmanned air
vehicles (UAVs). Unmanned platforms of the 21st century are being driven by the requirements
of civilian, government, and military objectives alike and have been made possible by the
technological advances yielded by a century of manned flight (Pines & Bohorquez, 2006). The
latest innovations in UAVs have given rise to a new class of aircraft called a micro air vehicle
(MAV) which is defined to be less than 6 inches in any given dimension with a gross takeoff
weight of 200 g or less (Pines & Bohorquez, 2006). This new class of UAV presents even
greater options for surveillance and reconnaissance operations in a wide variety of environments
which have been previously been inaccessible or potentially hostile to both manned and
unmanned flight platforms from enclosed urban environments to the low oxygen atmospheric
environment of Mars.
This proposed project investigates the capabilities and design considerations of current
MAV flight platforms to assess their effectiveness at meeting the expanding requirements of
UAV flight for both terrestrial and space applications. Specifically, Earth-based remote sensing
mission requirements and the flight requirements for successful MAV operations on Mars will be
determined and current MAV platforms will be investigated with a focus on their ability to meet
one or both mission profiles. The flight efficiency and performance characteristics of current
MAV platforms will be examined using an ANOVA statistical analysis and compared to the
flight efficiency and performance characteristics of existing mission capable large-scale UAV

platforms in order to understand the effectiveness of the emerging flight characteristics of recent
MAV designs. Next generation aerodynamics research and MAV prototypes using low
Reynolds number flight and biokinetic flight mechanics will be evaluated for their future ability
to fulfill the terrestrial mission and Mars mission requirements.
Program Outcomes
PO#1
Students will be able to apply the fundamentals of air transportation as part of a global,
multimodal transportation system, including the technological, social, environmental, and
political aspects of the system to examine, compare, analyze and recommend conclusion.
 Micro air vehicles (MAVs) are an emerging technology which will have a variety
of applications particularly for low Reynolds number and low oxygen flight
conditions (Michelson & Naqvi, 2003). The future role for MAVs will be
explored as part of the air transportation system on Earth and for use on future
Mars missions.
 The technological design aspects required for consistent flight of MAVs in the
Mars and Earth environments will be examined with respect to flight efficiency
and performance characteristics of current MAV platforms and prototypes. As of
2012, the Federal Aviation Agency (FAA) has been tasked with the integration of
unmanned aircraft into the United States’ civil airspace (Federal Aviation
Administration, 2013).
 The social impacts of widespread use of MAVs for urban surveillance focus
particularly on privacy concerns of governments and civilians alike and will be
analyzed with respect to the impacts present in known traditional UAV aircraft.

 The environmental concerns of unmanned aircraft integration will be analyzed
using existing studies on UAV impacts, and space-based environmental aspects
will be addressed using current international space legislation.
 The political aspects of use of MAVs for terrestrial surveillance and
reconnaissance missions as well as for future Mars exploration will be discussed
by means of relevant existing unmanned aircraft and space legislation.
PO#2
The student will be able to identify and apply appropriate statistical analysis, to include
techniques in data collection, review, critique, interpretation and inference in the aviation and
aerospace industry.
 The flight efficiency and performance characteristics of current micro air vehicle
(MAV) platforms will be analyzed to determine overall MAV suitability for the
expanding mission requirements of atmospheric and spaceflight unmanned
aircraft using an ANOVA statistical analysis.
 Terrestrial mission requirements will be identified using current Department of
Defense and Defense Advanced Research Projects Agency (DARPA) unmanned
aircraft development reports. National and international developmental
performance requirements will be reviewed. Mission requirements for a future
Mars mission will be identified using NASA Innovative Advanced Concepts
reports and current NASA Mars mission objective reports and MAV suitability
for the Mars environment will be assessed.

 A comparison of flight efficiency performance characteristics of MAVs will be
conducted using existing flight data collected from operational MAV and UAV
aircraft.
 MAV suitability for future Department of Defense mission requirements and
MAV flight capability for the Mars environment will be assessed using
interpretation from the results of an ANOVA statistical analysis.
PO#3
The student will be able across all subjects to use the fundamentals of human factors in all
aspects of the aviation and aerospace industry, including unsafe acts, attitudes, errors, human
behavior, and human limitations as they relate to the aviators adaption to the aviation
environment to reach conclusions.
 The human factors of piloting and maintaining micro air vehicles (MAVs) will
be discussed using known data from traditional UAVs, and the considerations of
smaller size constraints in MAVs will be assessed with respect to human
limitations inherent in command and control of MAV aircraft.
 Federal Aviation Administration (FAA) and Department of Defense accident
studies on existing UAV operations will be analyzed to determine the strengths
and weakness of unmanned aircraft relating to unsafe acts.
 Hazardous attitudes affecting the decision making processes of existing UAV
crews will be assessed and related to similar concerns for future MAV operations.
 Existing and experimental MAV and UAV autonomous, semi-autonomous, and
non-autonomous control systems will be investigated for their design

effectiveness in relation to reducing human error and enhancing remote piloting
options for MAV platforms.
 Reports on human behavior from the Department of Defense and Federal
Aviation Administration (FAA) will be assessed with respect to the flight
operations and crew selection of existing UAVs and assessed for application in
future MAV missions.
PO#4
The student will be able to develop and/or apply current aviation and industry related research
methods, including problem identification, hypothesis formulation, and interpretation of findings
to present as solutions in the investigation of an aviation / aerospace related topic.
 Statistical analysis will be conducted using an ANOVA analysis on micro air
vehicle (MAV) flight design characteristics to accept or reject the hypothesis that
there is a statistically significant difference between MAV flight efficiency and
performance parameters and the parameters of currently operational UAVs.
 Current UAV aircraft have been technologically limited to operations in
environments and aerodynamic conditions similar to those of traditional manned
aircraft (Pines & Bohorquez, 2006). A statistical difference between MAV and
UAV flight design characteristics will identify the existence of a new class of
UAVs that is capable of operating in currently unattainable flight conditions.
 Interpretation of flight characteristics data will be performed with respect to
suitability of MAVs to perform the mission requirements for operations in
terrestrial remote sensing and future Mars exploration. Design data for existing

MAVs and currently operational UAVs will be acquired from flight specification
data for existing flight platforms.
PO#5: Aeronautics
The student will investigate, compare, contrast, analyze and form conclusions to current
aviation, aerospace, and industry related topics in aeronautics, including advanced
aerodynamics, advanced aircraft performance, simulation systems, crew resource management,
advanced meteorology, rotorcraft operations and advanced aircraft/spacecraft systems.
 The design characteristics of current micro air vehicle (MAV) flight platforms
will be explored through analysis using advanced aircraft performance flight
data.
 Advanced aerodynamics research in the field of low Reynolds number flight
capabilities for MAVs will be examined for the enhancement of MAV technology
for future unmanned missions on Earth and Mars.
 The meteorological effects present in terrestrial hazardous environments and the
low oxygen environments of Mars will be analyzed to determine flight
requirements for the design of MAVs in each respective environment.
 Rotorcraft operations of flapping and rotor MAV designs will be discussed, and
rotor design benefits and limitations will be investigated for existing and future
MAV aircraft.
 Emerging materials technology and understanding of low Reynolds number
aerodynamics used for existing and future MAV designs with be determined with
respect to known advanced aircraft/spacecraft systems.

 This student did not take classes in simulation systems or crew resource
management.
PO#11: Space Studies
The student will investigate, compare, contrast, analyze and form conclusions to current
aviation, aerospace, and industry related topics in space studies, including earth observation
and remote sensing, mission and launch operations, habitation and life support systems, and
applications in space commerce, defense, and exploration.
 Earth observation using MAVs particularly for surveillance and reconnaissance
operations will be explored using known operational UAV data and Department
of Defense reports for future MAV mission requirements.
 Remote sensing sensor capabilities will be explored given current size and power
constraints of MAV designs for terrestrial and spaceflight purposes.
 MAV integration for a manned future mission to Mars will be explored for use
during space mission operations. Requirements for launch to Mars will be
determined based on current NASA Innovative Advanced Concepts reports and
current NASA Mars mission objective reports.
 Maintenance and support for MAVs during a manned Mars mission and possible
uses for exploration and manned habitation of Mars will be discussed.
 The uses of MAV for space commerce, defense, and exploration will be
analyzed using current information on MAV prototypes as well as DoD and
NASA reports on MAV capabilities for hostile environments of space and
terrestrial defense.

Introduction
Micro Aerial Vehicles have been in development for more than a decade spurred by
recent technological advancements in aerodynamics and materials science (Carey, 2007).
Unmanned Aerial Vehicles (UAVs) have been in operation since the 1950s during World War I
(Mueller, 2007). Functional MAVs the size of a human hand or smaller yield the promise of a
wider array of capabilities previously unattainable by their larger UAV counterparts.
Advancements in MAV capabilities will greatly enhance mission possibilities for both terrestrial
surveillance and reconnaissance missions and remote sensing applications for planetary space
exploration. The classification of MAVs, their role in the global air transportation system,
human factors concerns relating to MAV design and operation, and low Reynolds number
aerodynamic flight design are developing areas of MAV aircraft operations that are vital to their
success for terrestrial military and civilian applications. The characteristics of MAVs which
cause them to be ideally suited as planetary space exploration vehicles are embodied by the
Georgia Tech Research Institute’s Entomopter MAV prototype. Exploration of extreme
environments both on Earth and Mars has the potential to be significantly enhanced through the
continued expansion of MAV aircraft and the small scale technologies associated with them.
DARPA Micro Air Vehicle Guidelines
The United States Micro Air Vehicle program has largely been driven by mission needs
of the Department of Defense. The Department of Defense has identified a need to develop
“autonomous, lightweight, small-scale flying machines that are appropriate for a variety of
missions including reconnaissance over land, in buildings and tunnels, and other confined
spaces. Of particular interest is the ability of these vehicles to operate in the urban environment

and perch on buildings to provide situational awareness to the warfighter.” (Pines & Bohorquez,
2006, pg. 290). An MAV design useful to the DoD’s needs additionally requires a cost effective
and efficient design that is simple to deploy and operate. The design and production of a micro
sized aircraft is a challenging prospect even with recent advances in small scale electronics and
materials. Therefore, the DoD initiated a series of MAV design challenges through the Defense
Advanced Research Projects Agency (DARPA) which provides development funding for the
most promising MAV prototype aircraft.
A Micro Air Vehicle (MAV) is a class of unmanned aerial vehicle (UAV) that has a
wingspan of 15 cm or less according to current DARPA Micro Air Vehicle program guidelines.
The first successful MAV was awarded a DARPA Small Business Innovation Research Phase 1
contract in 1996 and a Phase 2 contract in 1998 when AeroVironment successfully demonstrated
its electrically powered flying wing, the Black Widow MAV (Grasmeyer & Kennon, 2001). The
initial design challenge for MAVs was created in order to drive technological development of the
smallest aircraft possible that could operate a successful remote sensing mission. DARPA has
also initiated a program to develop even smaller Nano Air Vehicles (NAVs) which have similar
flight characteristics to MAVs, but NAVs have wingspans of 7.5 cm or less. However,
DARPA’s Nano Air Vehicle program has achieved fewer mission capable prototypes than its
MAV programs as power sources and materials needed for nano-sized aircraft are still not
efficient enough to produce aircraft able to perform a remote sensing mission. The
AeroVironment company was eventually awarded the DARPA Nano Air Vehicle SBIR Phase 1
contract in 2008 and SBIR Phase 2 in 2009 with its demonstration of a controlled, hovering, dual
flapping-wing NAV, the Hummingbird Nano Air Vehicle, which is still in the testing phase

(AeroVironment, 2009). The initial DARPA requirements for an MAV are as follows in Table
1.
Specification Requirements Details
Size <15.24 cm Maximum dimension
Weight ~100 g Objective GTOW
Range 1 to 10 km Operational Range
Endurance 60 min Loiter time on station
Altitude <150 m Operational Ceiling
Speed 15 m/s Maximum flight speed
Payload 20 g Mission dependent
Cost $1500 Maximum Cost
Table 1. MAV Design Requirements (Pines & Bohorquez, 2006, p. 292).
The FAA regulates the national airspace and the air transportation system. The FAA has
integrated existing UAVs into the national airspace under the classification of unmanned aircraft
systems, which is defined to include unmanned aerial vehicles and micro air vehicles (FAA,
2013). Analysis of the current air transportation system and the human factors associated with
UAVs is directly applicable to MAVs due to their joint classification as unmanned aircraft
systems.
The Air Transportation System: FAA National Airspace Regulations for Unmanned Aerial
Vehicles
The need for FAA certification and oversight of UAVs has grown since civilian and
commercial interests have increased along with overall UAV capabilities. The Teal Group
estimates that governments and businesses will spend $89 billion on UAV systems through 2023
(Werner, 2014). The FAA has created a comprehensive plan describing the requirements for
integrating UAVs in the present national airspace, and the FAA Modernization and Reform Act
of 2012 sets benchmark dates for integration. The FAA Modernization law fails to set a deadline
for regular UAV flight operations. The law is further limited by the assumption that UAVs will
be operated by human pilots flying the aircraft from external ground sites without any mention of

use of autonomous or semi-autonomous control interfaces. Thirteen U.S. states have already
passed laws restricting UAV operations because of safety or privacy concerns with more states in
the process of following suit. The Aerospace Industries Association expects that conducting
routine UAV operations with an FAA filed flight plan without additional restriction will become
a reality sometime beyond 2025 (Werner, 2014).
The United States Congress included “unmanned aerial vehicles” in the wording of their
2003 Vision 100 – The Century of Aviation Reauthorization Act which outlines specific areas of
FAA development necessary for the Next Generational Air Transportation System (NextGen) to
accommodate the certification and operation of technological improvements to the present
national airspace. The FAA’s current policy on UAV flights was issued in 2007 and prohibits
operation of any UAV flights in the national airspace without a specific authority. The policy
pertains to both public and private unmanned aircraft. The FAA has employed two methods of
granting authority to operate UAVs: Certificate of Waiver of Authorization for private entities
and special airworthiness certificates for public entities to test their experimental stage aircraft.
The concern for these case-by-case basis methods of FAA certification is that the timeline
involved in securing FAA flight permission is much too long to allow the development of
civilian UAV operations (Elias, 2012).
Air Transportation System: Infrastructure Concerns
The Next Generation Air Transportation System Unmanned Aircraft Systems Research,
Development, and Demonstration Roadmap, Version 1.0, identifies the critical areas of the
national airspace that will require updating in order to allow for functional integration of UAVs
(Next Generation Air Transportation System, Joint Planning and Development Office, 2012).
Current communications infrastructure, airspace operations, unmanned aircraft awareness and

certification, and human systems integration are the principal areas of focus for NextGen UAV
development.
At present, there are no communications traffic forecast models for additional UAV
usage. The communications capacity and performance impact of the integration of UAVs into
the existing communications network will need to be defined. Furthermore, civil UAVs will
require a protected safety frequency spectrum for their control system radio signals so as to avoid
signal hacking or interception. Performance requirements and standards for UAV control
systems communication have not yet been outlined by the FAA. Such standardization of
hardware and radio signals would assist the integration of UAVs into the national airspace (Next
Generation Air Transportation System, Joint Planning and Development Office, 2012).
Airspace operations of all current UAVs in the national airspace have maintained
separate automation systems including: collision avoidance, self-separation, and separation
assurance systems. Pilot, air traffic control, and automation roles will need to be better defined
and mandated by the FAA to facilitate the seamless operation of multiple automation systems in
the same air space. Data collection and development of a UAV safety program current does not
exist. Standardized safety analyses of UAVs would allow for useful accident reporting and
would provide a program for addressing UAV safety concerns in the national airspace. Sense
and avoid sensors required for all UAV aircraft are the present solution to avoiding the projected
increase of UAV collisions due to their small size and pilotless functioning. Standardization and
regulation of the sensitivity of such devices is required for their effective use to manage UAV
proximities during airspace operations (Next Generation Air Transportation System, Joint
Planning and Development Office, 2012).

Unmanned aircraft as a modern aircraft platform have design and operational
considerations that differ from those of manned aircraft. Awareness of these UAV differences is
crucial for their integration into the present airspace. UAVs often perform changes to their flight
trajectories multiple times during the course of operations without the benefit of a pilot on board
to oversee them. There exists no national system for tracking such minute changes through
current air traffic control methods. The certification process for UAVs is a time consuming and
outmoded process that does not take into account new and novel materials that have been
development in recent years. The rapid evolution of UAVs and UAV technology requires
updating of the present FAA policies regarding their certification. The unmanned nature of
UAVs relies heavily on the Global Positioning System (GPS) for their guidance, navigation, and
control information. The lack of a pilot on board creates the potential for a GPS error to produce
much greater consequences as there are currently no backup navigation systems accurate enough
for UAV flight control. Research on the potential for accidents produced by GPS errors need to
be performed in order to ensure the safety of the national airspace. The advanced avionics and
control software packages used by UAVs have not been standardized or defined. The safety and
reliability of these systems are important factors which need to be addressed for the complete
integration of UAVs with their manned counterparts in the national airspace (Next Generation
Air Transportation System, Joint Planning and Development Office, 2012).
Lastly, human systems integration is a vital aspect of the present airspace that has not yet
been adapted for UAV operations. Air traffic and airspace information require integration into
UAV ground control stations on a national scale. Particularly, monitoring of aircraft trajectories,
terrain avoidance, and weather will assist in UAV operations in the national air space. The levels
of automation vs. human control during routine UAV flight is not current regulated by the FAA.

Standardization and procedures outlined for automatic piloting of UAVs would help to mitigate
errors associated with use of multiple modes of UAV flight control. Communications and
potential hand-offs of unmanned aircraft between UAV ground control stations require
addressing. Ground Control Stations are not currently regulated by the FAA, and they should
demonstrate their ability to safely operate a UAV in the national airspace. Contingencies for
emergency situations which may arise during UAV operations have not been devised. Reliance
on present manned aircraft procedures and response checklists will not necessarily pertain to the
operations of UAVs especially where datalink or control communications are lost between air
traffic control, the UAV ground station, and the UAV. Better defined human systems interaction
will be a vital aspect for the inclusion of UAVs into the future air transportation infrastructure
(Next Generation Air Transportation System, Joint Planning and Development Office, 2012).
Air Transportation System: Privacy Concerns
The expanded surveillance capabilities of MAVs also increase the privacy concerns that
have been the topic of debate due to more widespread civilian use of UAVs. The sensor
payloads of conventional UAVs can include an array of imaging sensors including cameras and
electro-optical imagers, infrared sensors, synthetic aperture radar, and specialized environmental
sensors (Elias, 2012). This wide variety of sensors allows UAVs to be useful for diverse
applications, but raises concerns over intrusiveness of UAV use particularly during widespread
civilian operations. Privacy groups such as the American Civil Liberties Union and the
Electronic Privacy Information Center argue that use of UAVs with imaging sensors “could lead
to abuses in monitoring, tracking, and surveilling people throughout the courses of their daily
lives” (Elias, 2012, p. 19).

Privacy concerns have largely been raised concerning law enforcement and government
use of UAVs, but there is a growing case to be made for the possibility of commercial use of
drones with the expansion of FAA airspace regulations for UAVs (Elias, 2012). UAVs could
become intrusive in the hands of marketing firms, journalists, and private investigation firms.
Use of UAV surveillance in the commercial sectors is not subject to U.S. Fourth Amendment
rights when data collected is not being used by government organizations; however, it could still
be very intrusive to the civilian public. While the FAA has authority over airspace and flight
operations restrictions, it has an extremely limited authority over specific uses for civilian UAV
use (Elias, 2012).
Human Factors Concerning Operations of Unmanned Aerial Vehicles
Safety data for operational micro aerial vehicles is currently limited to prototype research
and small scope military deployment. However, the concerns faced by the emerging MAV class
are driven by the extensive safety data of operational UAVs to this point. While widespread
civilian use of UAVs remains restricted, the military has been using unmanned targeting drones
and UAV aircraft extensively since the 1950s (Elias, 2012). The Air Force Scientific Advisory
Board identifies the human/system interface as the greatest deficiency in current unmanned
aircraft designs in a review conducted in 1996 (Williams, 2006). More recent multiplatform
UAV studies support this assessment, but specific interface deficiencies have been seen to differ
across the greater array of UAV systems available. Unmanned aerial vehicles have a wide
range of capabilities which give them near limitless potential for use in the military and civilian
sectors alike. Proposed markets for this expanding class of aircraft include scientific data
collection, cross-country transport, and telecommunications services alongside the present UAV
markets of surveillance and defense. The wide array of possible flight services of UAVs are tied

together by the requirements of efficient operation whatever the use (McCarley & Wickens,
2004). In particular, the role of the UAV pilot has come under intense scrutiny with the recent
decision of the FAA to integrate UAVs into the national airspace (Federal Aviation
Administration, 2013). Human error has been found to be a major contributing factor to the
higher accident rates of UAVs as compared to conventional manned aircraft. This is in part due
to the fact that the UAV operator’s task in flying these aircraft is quite different to the piloting of
conventional aircraft in many respects. Current aviation standards and regulations for unmanned
flight in the United States national airspace only allow operation of UAV aircraft on a case-by-case
basis (Elias, 2012). A more thorough understanding of the requirements for the human
factors of all aspects of UAV flight is needed to produce safer and more effective UAVs if they
are to continue to expand into the national airspace.
The Department of Defense conducted a comprehensive ten year review of human factors
in military UAV accidents as mishaps using the Human Factors Analysis and Classification
System (HFACS). The “HFACS is a model of accident causation based on the premise latent
failures at the levels of organizational influences, unsafe supervision, and unsafe preconditions
predisposed to active failures (e.g. UAV operator error)” (Thompson, 2005 p. vi). In the case of
UAV human factors analysis using the HFACS, the focus is made on the aspects of UAV
operations that lend themselves to sources of error which may cause operator error in the first
place. Recommendations for system changes in order to remove the possibility of human error
from the operational system are then made. This methodology has proven more effective than
making changes to crew selection or training in order to compensate for the possibility of
mishaps which are inherent in the functioning of any complex system including UAV operations
(Thompson, 2005).

Unmanned aerial vehicles have demonstrated their capabilities to meet recent military
needs during mission in Iraq as a mixed fleet of no fewer than a hundred UAVS in ten distinct
mission profiles. The accident rates of these aircraft are startling particularly when compared to
manned flight: the United States Air Force’s RQ-1 Predator UAV was found to have a mishap
rate of 32 mishaps per 100,000 flight hours, the United States Navy and Marine Corp’s RQ -2
Pioneer accumulated 334 mishaps per 100,000 hours, and the United States Army’s RQ-5 Hunter
showed 55 mishaps per 100,000 hours. Comparatively, current general aviation mishap rates
average 1 mishap per 100,000 flight hours. The reliability rates of UAVs will have to increase
one to two orders of magnitude before they operate with the equivalent safety of general aviation
aircraft (Thompson, 2005). The RQ-1 Predator, RQ-2 Pioneer, and RQ-5 Hunter UAVs were
examined by one of the most comprehensive reviews of UAV mishaps to date, the Office of the
Secretary of Defense’s UAV Reliability Study which was issued in 2003. Collectively, these
UAV platforms were found to have 17% of their sources of failures be attributed to human
factors. While the total number of UAV mishaps remains much larger than for manned aircraft,
the contribution of human error to manned aircraft is 85% of sources of failures. This has been
attributed to the high degree of automation of systems in UAV aircraft even when remotely
piloted as well as the relatively high unreliability of all of the other systems necessary for UAV
flight (Thompson, 2005).
Operations using modern UAV aircraft are still in their infancy and currently utilize flight
technologies that are often still in the early stages of development. Focusing improvements on
the areas of flight automation and flight systems reliability could significantly reduce overall
human factors related accidents. The Office of the Secretary of Defense’s UAV Reliability
Study suggests that UAV operator situational awareness is often significantly reduced by the

complex nature of the human-machine interface used to remotely pilot UAV aircraft. The report
also recommended enhancements for UAV operator training through simulation in an established
ground control station environment which would help address the limited experience levels of
UAV operators and maintainers (Thompson, 2005).
Manned aircraft have been in operation for long enough to achieve a high degree of
reliability. Human factors concerns still pervade the sources of error in any airframe, but
manned aircraft have been developed through countless design iterations with a strong focus on
management and elimination of human errors and mishaps which might occur during the course
of operations. UAV aircraft present many challenges to human factors design that are quite
different from those found in manned aircraft which occur predominantly because the UAV and
pilot are not collocated (McCarley & Wickens, 2004). Human factors design challenges
primarily include issues with: displays and controls, automated system failures, and crew
composition and training.
Human Factors: Displays and Controls
The separation of a UAV and its operator causes a lack of sensory cues that are available
to the pilot of a manned aircraft. Direct sensory inputs from changes in the flight environment
that the UAV is operating in are instead replaced with artificial sensory information that is
relayed to the UAV operator via datalink containing the UAV’s sensor updates. The form that
UAV sensor information is relayed to the operator varies according to the UAV airframe in
question, but it is usually visual imagery with a severely restricted field of view. Physical
control system information, surrounding visual inputs, and sound are typically unaccounted for
in UAV information sent to its operator. This is referred to as “sensory isolation” experienced
by UAV pilots which is a major obstacle to the human-machine integration required for reliable

UAV flight. (McCarley & Wickens, 2004, p. 1). Solutions to the problem of sensory isolation
have come in changes to the displays and controls of UAVs. Multimodal displays are becoming
more prevalent due to proven improvements on UAV pilot situation awareness. One success has
been in the haptic relaying of turbulence information through the pilot’s joystick. Previously,
disturbances caused by turbulence were only relayed to the pilot through the graphic camera
image shaking on the edges of the field of view. Artificial vibration added to the joystick during
turbulence effects helped to achieve a simulated response that was comparable to that
experienced by manned aircraft pilots. The benefits of quickly relaying turbulence intensity and
timing helped particularly for approach and landing tasks (McCarley & Wickens, 2004).
Multimodal displays help to reduce the overall mental workload throughout the course of
a UAV mission by their ability to convey more flight and payload data of a UAV to its operator
in a shorter amount of time than with traditional displays. Not only does this make them
effective for removing sensory isolation effects from UAV operations, but they can also be used
to relieve UAV pilot fatigue through information overload. Tactile and sound displays are being
used in order to alert operators to system malfunctions and other emergency events. This helps
to remove this important information from the already crowded visual display interface
(McCarley & Wickens, 2004).
UAVs are particularly limited in the bandwidths that can be used to relay sensor
information between the vehicle and pilot. This typically results in low temporal and spatial
resolution images that are transmitted to visual displays. Transmission delays and radio
feedback also serve to reduce the overall quality of the sensor inputs given to the UAV pilot that
impair target tracking and other visually intensive operations. Data bandwidth limits imposed by
small scale UAV designs could potentially be alleviated through use of augmented reality or

synthetic vision systems that are still in the research and development stage. In particular,
augmented reality displays have shown to improve visual acuity through use of artificially
compiled visual inputs which leads to overall improvements in UAV flight control by an
operator (McCarley & Wickens, 2004).
Human Factors: Automated System Failures
The automation of flight controls for UAV aircraft has been a focal point for error
mitigation since the inception of remotely piloted aircraft. While automation is certainly an
important advancement for unmanned systems, it does not always provide greater reliability for
the performance of a UAV. The Global Hawk UAV is one of the largest military UAVs that has
been equipped with a fully automated taxiing, take off, and landing system. However, accidents
still occur involving flight-control automation. Even the most sophisticated automatic flight
control systems are still prone to responses that are difficult to anticipate during flight operations
because all possible contingencies of a given flight are difficult to foresee (Williams, 2006).
There is large variety of the extent to which UAV systems are automated. Many platforms have
very little automation and are flown manually by a pilot using remote stick and rudder controls.
Partially automated UAVs provide flight parameter options through a control interface in the
ground station that are selected by the pilot through the course of the flight. Fully automated
UAVs use autopilot controls using preprogrammed flight coordinates during each phase of the
mission, and the flight progress is monitored by the UAV operator for each phase. Data on the
incident of flight accidents involving human error using autonomous control pinpoint automatic
takeoff and landing procedures during these phases of flight. This is predominantly because of
error associated with transfer of pilot control between manual and autopilot modes. Another
contributing factor is ambiguity about the amount of aircraft autonomy that is integral for the

design of automatic systems that are effective in a wide array of contingences (McCarley &
Wickens, 2004).
Human Factors: Crew Selection and Training
UAVs are controlled through a variety of crew setups depending on the characteristics of
the aircraft and mission parameters. Many military reconnaissance missions require a crew of
two operators: one for payload sensor control and one for aircraft control. The separation of
workloads has been found to decrease the amount of errors and increase efficiency for the
functioning of UAVs regardless of mission where conventional UAV displays are the methods of
control. However, future advancements in displays and controls are projected to allow for
piloting of most UAV aircraft by a single operator or even use of a single operator to effectively
supervise the operations of multiple autonomous UAV aircraft. As display and control
technologies become more advanced, however, there are still other elements of UAV operations
where human factors play a role. Hand-off of controls between crews of UAV operators still
presents an area where errors are routinely made due to challenges with inter-crew
communication and coordination. The selection and training of effective UAV operators has not
been thoroughly developed even in the military. Research studies have suggested a positive
correlation between manned flight experience and remote piloting of the United States Air Force
Predator UAV. Currently, even a private pilot rating is not required for all UAV operators in the
military. Ground school UAV training and simulation have correspondingly not been very well
developed. Adequate training and preparation for UAV pilots is necessary if human error is to
be reduced for any UAV platform operating today or in the future (McCarley & Wickens, 2004).

Human Factors: Recommendations of the Department of Defense
The remote operation of UAV aircraft creates human factors challenges in all aspects of
flight operations. The majority of flight operations research involving the human factors of
UAV flight has been pursued by the Department of Defense to date. Accordingly, the Secretary
of the Department of Defense has mandated reduction of the total number of mishaps and
accident rates by a minimum of 50%. In order to accomplish this, the armed forces have been
recommended to “evaluate and optimize UAV operator selection and training criteria and the
ground control station interface design”, enhance current UAV operator training programs to
“include a specific curriculum emphasis on crew resource management”, perform an analysis of
UAV crew manpower requirements and workstation design, and refocus all Department of
Defense human error analysis “from immediate mechanical failures as the cause of UAV
mishaps to failures in the organizational culture […] for UAVs” (Thompson, 2005, p. vii).
Additionally, technological advancements for the human-machine interface used for UAV
operations show promise. The ability to successfully relay UAV sensor information to its pilot
more effectively will ultimately result in the reduction of pilot sensory overload that pervades the
current UAV interfaces. The improvement of automated UAV systems will also help reduce the
pilot workload. However, a better understanding of the extent to which automated control of
UAV systems is reliable and effective is needed to prevent human error arising from automation
itself. Crew selection and training for UAV crews remains to be well defined or prioritized thus
far. Human factors as a source of UAV mishaps and accidents will only be reduced by the active
pursuit of changes to the operational culture, effective crew resource management, and updates
to displays and controls technology of UAVs.

Statistical Analysis: Micro Air Vehicles as an Emerging Class of Unmanned Aerial Vehicles
Advances in small scale electronics and materials technology have allowed for the design
of increasingly smaller aircraft and aircraft systems. In particular, the field of unmanned aerial
vehicles (UAV) has recently undergone a rapid expansion due to the development of such
technology. Department of Defense research contracts and competitions have driven the
performance characteristics of UAV prototypes to new small scale sizes, and DARPA has
defined a new subclass of UAV called the micro air vehicle (MAV). “As a new class of air
vehicle, these systems face many unique challenges that make their design and development
difficult” (Pines & Bohorquez, 2006, p. 290). The purpose of this statistical analysis is to accept
or reject the hypothesis (H0) that there is a statistically significant difference between the aircraft
flight efficiency and performance characteristics of currently operational MAVs and UAVs. To
give a basis for this comparison, the additional hypotheses for the similarities of flight
characteristics within the individual classes of MAV and UAV must also be determined. The
analysis for variance between performance parameters was conducted using an Analysis of
Variance (ANOVA) for a single factor correlation.
The initial set of data that was analyzed included flight efficiency and performance
characteristics from a representative data set from MAVs which have been successfully
demonstrated during the DARPA Phase I MAV competition. Table 2 is adapted from the full
parameter chart. See Appendix A for the full data set.
Vehicle Properties GTOW, g Cruise Speed, m/s
Wing/Disc loading,
N/m²
Wing span or rotor
diameter, cm Endurance, min
Black Widow (AeroVironment) 80 13.4 40.3 15.24 30
Hoverfly (AeroVironment) 180 17.5 70 18 13.2
LUMAV (Auburn University) 440 5 185 15.24 20
Micro-Star (Lockheed-Martin) 110 14.5 70.9 22.86 25
Microbot (CalTech) 10.5 5 40 15.24 2.1
MICOR (UMD) 103 2 25 15.24 3

Table 2 MAV Design and Performance Parameters. Adapted from (Pines & Bohorquez, 2006, p.
293)
The results of a single factor ANOVA for Table 2 for an α of 0.05, which corresponds to
a 95% confidence level, demonstrates large variances between flight parameters. Overall, the P-value
determined by the ANOVA is 0.0085. This is much less than the selected α of 0.05. This
indicates that the hypothesis that flight parameters within the MAV class are similar is rejected,
or H0≠0. The null hypothesis is rejected for the similarities within MAV characteristics. See
Appendix C for the Single Factor ANOVA Analysis of MAV Design and Performance
Parameters.
Data collected from the American Institute of Aeronautics and Astronautics annual UAV
Roundup was used to analyze UAVs currently deployed in the United States of America by the
flight and performance characteristics of endurance, range, and flight ceiling. As the
characteristics of endurance and range involve the design specifications used in the MAV data
set in their computation, these analysis variables are comparable. Table 3 is adapted from the
full chart of data.

Endurance (hr) Range (mi) Ceiling (ft)
Fixed-Wing UAV AAI Shadow 400 5 200 3353
AeroVironment RQ-11B Raven 1.5 6 500
AeroVironment RQ-14 Dragon Eye 1 3 152
Applied Research Associates Nighthawk 1 6 11000
BAI Systems XPV-1 Tern 4 64.4 3048
DRS Unamnned Technologies Sentry HP 6 70 10000
DRS Unamnned Technologies RQ-15 Neptune 4 50 8000
Elbit Systems of America Hermes 450 18 120 18000
Elbit Systems of America Skylark I-LE 3 9 15000
General Atomics I-GNAT ER/Sky Warrior 40 155 25000
General Atomics Predator (RQ-1A/MQ-1) 40 675 25000
General Atomics Guardian 27 1151 50000
Lockheed Martin Desert Hawk III 1.5 9.3 1000
Northrop Grumman Bat 12 12 989 18000
Northrop Grumman MQ-5B Hunter 15 166 6096
Textron Defense Systems Shadow 200 9 90 15000
Rotary UAV AAI RQ-7B Shadow 200 TUAS 9 125 4572
AAI Shadow 600 14 200 4877
Guided Systems Technologies SiCX-10E 0.416666667 0.5 12000
Kaman Aviation K-MAX UAT 10 115 29000
MMIST CQ-10A 15 500 18000
Table 3 Deployed UAV Flight and Performance Characteristics. Adapted from (American
Institute of Aeronautics and Astronautics, 2013 pp. 26-31)
The results of a single factor ANOVA for Table 3, for an α of 0.05, also displays large
variances between flight parameters. Overall, the P-value determined by the ANOVA is 1.23 x
10-8. This is much less than the selected α of 0.05, and more than five orders of magnitude
smaller than for MAVs. This indicates that the hypothesis that flight parameters within the
currently deployed UAV class are similar is rejected, or H0≠0. The null hypothesis is rejected
for the similarities within UAV characteristics. See Appendix D for the Single Factor ANOVA
Analysis for Deployed UAV Flight and Performance Characteristics.
The size range for currently deployed UAVs in the United States is extremely wide
ranging. Therefore, an additional analysis for similarities in the UAV class was completed as a
means of comparing UAVs within the same size range. Small UAVs as determined by the
American Institute of Aeronautics and Astronautics where analyzed for their parameter
similarities. Table 4 Small Size UAV Performance and Flight Characteristics. Additional design

parameter data in the categories of wingspan and maximum takeoff weight were added from
individual manufacturers’ data specification sheets. See Appendix B for the full adapted UAV
chart.
Designation Endurance (hr) Range (mi.) Ceiling (ft) Wingspan (ft)
Max Take-Off
Weight (lbs)
Orbiter 3.0 31.1 18,000 7.2 15.4
RQ-11B Raven 1.5 6.0 500 4.5 4.2
RQ-14 Dragon Eye 1.0 3.0 152 3.8 5.9
RQ-20A Puma AE 2.0 3.0 500 9.2 13.5
Wasp AE 0.8 3.0 500 3.3 2.9
Bala B 0.8 10.0 10,000 5.4 3.5
Jago B 1.0 20.0 10,000 5.4 12.0
Invenio 0.8 10.0 10,000 4.5 3.5
Nighthawk 1.0 6.0 11,000 2.2 1.9
Skate SUAS 1.5 3.0 400 2.0 2.2
Coyote 1.5 23.0 20,000 5.7 12.1
XPV-1 Tern 4.0 64.4 3,048 11.3 24.3
Dragon 3.0 50.0 10,000 8.0 95.0
RQ-15 Neptune 4.0 50.0 8,000 7.0 135.0
T-Hawk 0.8 3.6 10,000 1.2 20.0
Bat 4 12.0 10.0 10,000 13.0 125.0
Super Bat 10.0 10.0 10,000 8.5 34.0
V Bat 10.0 10.0 15,000 8.0 55.0
SR5 0.3 2.5 1,640 2.3 4.0
SR20 1.3 6.0 4,900 5.1 24.5
Merlin 200 5.5 60.0 11,000 16.0 161.0
Rotor Buzz 1.0 15.0 6,000 11.7 265.0
Silhouette 1.0 7.0 10,000 8.3 28.5
Table 4 Small Size UAV Performance and Flight Characteristics. Adapted from (American
Institute of Aeronautics and Astronautics, 2013 pp. 26-31)
The results of a single factor ANOVA for Table 4, for an α of 0.05, similarly contains
large variances between flight parameters of small sized UAVs. Overall, the P-value determined
by the ANOVA is 6.09 x 10-22. This is much less than the selected α of 0.05. This indicates that
the hypothesis that flight parameters within the Small Sized UAV class are similar is rejected, or
H0≠0. The null hypothesis is rejected for the similarities within UAV characteristics. See

Appendix E for the Single Factor ANOVA Analysis of MAV Design and Performance
Parameters.
The results of all three ANOVA analyzes demonstrate the large variation between flight
and performance characteristics of MAVs and UAVs. While this does not lend itself to
comparing the two classes of aircraft by their characteristics, it does suggest an overall defining
characteristic of unmanned aircraft. Namely, the functionality and capabilities of unmanned
aircraft are extremely wide ranging. DARPA has defined the physical size of MAVs for their
continued small scale research, but both UAVs and MAVs have a vast array of configurat ions
regardless of their size. It is this characteristic which most defines their potential.
Terrestrial MAV Design Considerations
Micro Aerial Vehicles can operate in a wider variety of environments than their present
UAV counterparts. The U.S. military is particularly interested in MAVs which could have the
ability to explore “underground bunker and other structures” (Georgia Tech Research Institute,
2013, p. 1). The development of an insectoid entomopter MAV design concept is being
developed at Georgia Tech alongside its Mars version and would also provide a hybrid
air/ground platform for surveillance of tight spaces and low oxygen environments on Earth
(Georgia Tech Research Institute, 2013).
Mars Exploration MAV Design Criteria
As the nearest planet to Earth, Mars has been the focus of scientific exploration for the
last twenty-five years. Werner von Braun even considered a rocket design for Mars as early as
1953, but it wasn’t until the success of the Viking program in the 1970s that Mars flight was
considered a real possibility (NASA Institute for Advanced Concepts, 2002). To date, most of
the exploration of Mars has been achieved through use of orbiting spacecraft or surface rovers.

Orbiters can produce imaging data over a wide area and over extended periods of time, but the
data is severely limited in resolution (NASA Institute for Advanced Concepts, 2002). Mars
rovers have more data and sample collection options and can image small areas in great detail,
but they are constrained by their ability to traverse the terrain and obstacles that occur in their
area of operation. An airborne exploration platform would enable high resolution imaging of the
Martian surface over large areas with enough maneuverability to traverse canyons and other
obstacles that have hampered the operations of surface rovers. However, flight on Mars presents
numerous challenges which, until the recent technological breakthroughs of MAV technology,
have made a viable airborne platform impossible.
The Martian environment is particularly inhospitable to traditional aircraft. The Mars
atmospheric density is very low at nearly 1/70th of that found on Earth (NASA Institute for
Advanced Concepts, 2002). This is similar to the Earth’s density at one hundred thousand feet
about sea level (Georgia Tech Research Institute, 2013). Lift is proportional to atmospheric
density, wing area, and forward velocity. Flight in the thin Mars atmosphere in a fixed wing
aircraft would either require a large wing span or a very high velocity in order to generate
enough lift to even leave the surface (NASA Institute for Advanced Concepts, 2002). The Mars
atmosphere is also completely different in composition to that of Earth’s, and it is composed of
ninety- five percent carbon dioxide with only slightly more than one percent oxygen (Georgia
Tech Research Institute, 2013). This makes use of oxygen-breathing engines impractical. The
engines used on Mars are better suited to the atmospheric composition if they are chemically or
electrically propelled. Rotorcraft are also heavily affected by air density and composition. The
speed of sound in carbon dioxide is twenty percent lower than in Earth’s oxygen rich atmosphere
(Georgia Tech Research Institute, 2013). Propellers and rotors, therefore, spin much slower on

Mars while producing lower lift and greater shock waves. Temperatures during the course of the
Martian day vary significantly. They rise to negative twenty degrees Celsius and fall below
negative one hundred and forty degrees Celsius in a single day (Georgia Tech Research Institute,
2013). These extreme temperature shifts make materials and fuel selection a particular challenge
for any aircraft operating on Mars. The lower density, low oxygen environment, and severe
temperatures on Mars are obstacles that have hindered traditional airborne platforms for
exploration of the planet’s surface. MAVs, on the other hand, are particularly well equipped for
flight in these regimes.
Case Study: Georgia Tech Research Institute’s Entomopter for Earth and Mars
Exploration
The flight efficiency of biological flyers far outstrips the performance achieved by even
the most efficient of aircraft manned or unmanned. Recent advancements in small-scale flight
have been achieved largely due to the availability of micro-sized technology that provides the
capability to mimic the flight mechanisms and power outputs of bird- and insect- like flight in
micro air vehicle aircraft. The area of biomimetics has been growing due to recent successes of
small-scale robotic vehicles. The term “biomimetics” refers to any “engineering process or
system that mimics biology” (Paulson, 2004, p. 48). Increases in the flight efficiency of
biomimetic MAVs have already been achieved through the first wave of successful designs for
MAVs which focused primarily on their feasibility for flight with limited operational testing.
Further refinement of MAV technology seeks to take their designs beyond feasibility. The
Entomopter MAV being developed by Georgia Tech Research Institute has been granted
numerous research contracts by the Air Force Research Laboratory, the DARPA/DSO
Mesomachines program, and the NASA Institute for Advanced Concepts to develop its platform

for a variety of future mission operations including use for Earth-based surveillance and as a
Mars exploration flyer (Michelson, 2002).
The term “entomopter” takes its meaning from biological flight modes. Birds fly using a
process called “ornithopter” while the beating of insect wings is the process known as flight by
“entomopter” (Azuma, 2006). Insects are generally much smaller than birds, with body weights
of between one and ten grams. Their wings are on a much smaller dimensional scale which
causes the flight mechanisms of insects to differ from those of birds. Their wing beating
frequency is more than 10Hz higher, resulting in a wing loading of less than 10M/m².
Consequently, the Reynolds number for insect flight is even lower than for bird flight with a
value less than 10³ which produces an extremely low flight speed that is prone to wind and other
atmospheric effects (Azuma, 2006). Georgia Tech Research Institute’s Entomopter design is
based specifically off of the hawkmoth (Manduca sexta) for its wing aerodynamics in order to
benefit from the strengths inherent in insect-like flight (Michelson, 2002). The low wing loading
and low flight speed allow for the Entomopter MAV to be easily carried by the wind, maneuver
with enhanced accuracy, and produce a high amount of lift per power output (Azuma, 2006).
The Entomopter design is particularly well suited for operation in a variety of low
Reynolds number environments. The Department of Defense has an interest in the Entomopter
development program for the future potential for swarms of Entomopter MAVs to rapidly deploy
to areas that have previously been inaccessible to traditional flight platforms such as indoors or
in deeply buried underground facilities. NASA’s interest in the Entomopter concerns its use as a
flyer for future Mars exploration (Michelson, 2008). The environments of both Earth’s
inaccessible locations and the Mars surface have uniquely similar characteristics which make the

Entomopter ideally suited for missions either terrestrial or Martian. See Table 8 for a
comparison of Earth and Mars atmospheric physical properties.

Earth Mars (equator)
Gas Composition (volume
ratio [%])
N2 78.1
O2 20.9
Ar 0.9
H2O 0~2
CO2 95.3
O2 0.1
N2 2.7
Ar 1.6
Temperature [K] 298 270
Pressure [Pa] 1.014 x 105 6.0 x 102
Density [kg/m3] 1.17 1.18 x 10-2
Speed of sound [m/s] 345 220
Viscosity coefficient [Pa*s] 1.86 x 10-5
1.36 x 10-5
Acceleration of gravity [m/s2] 9.8 3.78
Ratio of specific heats 1.4 1.34
Table 8. (Shimoyama, 2006, p.8)
The Entomopter has an anaerobic propulsion system which allows it to fly without the
need for oxygen in its flight environment. Its design includes multiple modes of transport
including flight, crawling, and swimming which give it a versatility for exploration unlike any
other flight platform currently in operation. The design of the Entomopter MAV follows the
hawkmoth’s low Reynolds number flight profile; therefore, it is especially useful for flight in
such regimes which exist on both Earth and Mars. The Entomopter’s size and autonomous
configuration are achieved through use of biomimetic, chemically fueled, reciprocating muscle
tissue which the Air Force Research Laboratory has currently contracted for its fourth generation
of performance refinement and size reduction (Michelson, 2002). The extensive operational
capabilities of the Entomopter MAV multimode autonomous robot for the most extreme of
environments has led to the simultaneous development of two Entomopter prototypes by Georgia
Tech Research Institute, each designed for exploration and operation: the Earth-based terrestrial
Entomopter MAV and the Mars-based Mars Flyer Entomopter MAV.

The Rationale for a Flapping Wing Terrestrial Entomopter
Aerial reconnaissance using conventionally sized unmanned aerial vehicles have been
widely successful for a variety of missions including operations requiring a low possibility of
detection. Even large UAVs are able to avoid detection when flying several thousand feet above
their targets. Their size also allows them to utilize state of the art optics hardware which allows
for real time recording of high resolution video and infrared images on UAV platforms such as
the Predator and Global Hawk. While micro air vehicles have a smaller radar signature for
stealth missions, they are inherently limited by their size when it comes to flight range, weather
hazards, and the payload weight they are able to carry. Therefore, the MAV is a poor choice of
platform for replacement of conventionally sized UAVs for outdoor missions. Their strengths,
however, make them ideal for addressing the need for a reconnaissance platform for indoor
environments of which there are none with the present UAV platform options (Michelson, 2002).
Terrestrial UAV missions have been unable to operate in indoor and constricted space
environments to date. MAVs are small enough in size to operate in these environments, and a
flapping wing MAV would have many advantages over a fixed wing configuration. Fixed wing
aircraft require either large wings, high forward velocities, or powerful engines in order to
produce lift (Michelson & Reece, 1998). Indoor operations prohibit high speed flight as the
MAV must be able to avoid obstacles while maintaining surveillance operations. Larger wings
quickly increase the size of the MAV and ultimately prevent MAV operation in confined spaces.
Turbofans, propellers, and other rotors used to provide air circulation over a wing are inefficient
at power use and severely limit the flight time of MAVs; therefore, they are not ideal for lift
generation of MAVs (Michelson & Reece, 1998).

Flapping wing flight is particularly suited to the operations of confined space MAVs.
Flapping wing flight produced a high lift with a comparatively low power output. Hovering
produced by rotor flight is both inefficient and noisy which is not suited to possible stealth
surveillance operations while hovering produced by flapping is extremely quiet due to a greater
dissipation of the wind vortices produced. Flapping wings are also particularly well suited to
slow and hovering flight which allows for short take-off and landing and greater maneuverability
in confined spaces (Michelson & Reece, 1998).
The Earth-based Terrestrial Entomopter Micro Air Vehicle
The urban indoor mission environment requires multimode vehicles such as the
Entomopter MAV that can fly, crawl, and swim with an autonomous navigation system in order
to rapidly negotiate building infrastructure. The indoor Entomopter MAV surveillance mission
also requires the MAV to operate at a much closer proximity to its target than for outdoor
missions. The increased stealth footprint for a small-scale MAV platform in such an enclosed
location gives it a significant advantage over conventional remote surveillance platforms. The
flight modes of both rotary and flapping wing aircraft are particularly well suited to flight in
confined spaces due to their ability to take off and land vertically and maneuver at a slow
airspeeds. Flapping wing flight has the advantage over rotary wing flight as the mechanical
design for a flapping wing MAV is less physically complex while highly energy efficient when
compared to a rotary MAV with similar capabilities (Michelson, 2002).
The terrestrial Entomopter operates using a highly efficient biomimetic propulsion
system, the reciprocating chemical muscle. “The [reciprocating chemical muscle] is an
anaerobic, ignitionless, catalytic device that can operate from a number of chemical fuel sources”
(Michelson, 2002, p. 484). The reciprocating chemical muscle program at Georgia Tech

Research Institute was originally to determine its feasibility for use in robotics. The program has
undergone additional refinement and size reduction during the DARPA/DSO program to
determine the reciprocating chemical muscle’s ability to meet the flight requirements of the
Entomopter. Its current design iteration demonstrates the capacity to generate enough power and
speed for the Entomopter’s flapping wing flight (Michelson, 2008).
The Entomopter uses flapping wing flight as a means to generate lift. The dual wing
configuration has been modeled after the hawkmoth, but they have been significantly modified
for use in conjunction with the reciprocating chemical muscle propulsive system. The wing
shape has been simplified from the hawkmoth’s mechanically complex structure which allows
for easier manufacture and active flow control during flight. The reciprocating chemical muscle
is connected to the wings, and it produces a wing beat using simple harmonic motion that
produces velocity, yaw, pitching, and roll changes. These flight maneuvers achieved solely
through lift modification through airflow about the wings using the waste gas output of the
reciprocating chemical muscle (Michelson, 2002).
Navigation of the Entomopter using as power efficient a system as possible is crucial to
its successful use for the reconnaissance and surveillance of confined indoor spaces. Complex
navigation systems typically require more power than can be stored on most MAV aircraft to
date. However, the navigation control of an MAV indoors must be as real time and accurate as
possible in order to effectively maneuver around obstacles that the MAV might encounter. Due
to the small size of the Entomopter, long communications antennas cannot be used as they do not
fit on the aircraft. Remote operation of an MAV inside a building is inhibited due to the loss of
transmitters and receivers between walls as well as the inability for a remote pilot to see the
MAV from outside of the target area. Therefore, an autonomous navigation system is the only

viable means of navigation for an indoor reconnaissance mission (Michelson, 2008). The
Entomopter uses a gas operated ultrasonic transmitter for obstacle avoidance and altitude sensing
that works similar to the ultrasonic methods of navigation of bats. Waste gas from the
reciprocating chemical muscle propulsion system creates a frequency-modulated continuous
wave that is picked up by the Entomopter’s finely tuned avoidance system sensors and returned
as a homing signal output. An obstacle in front of the Entomopter will cause an automatic signal
to fly to avoid the nearby area, or it will trigger an automatic all clear signal will be sent in order
to continue along its flight path (Michelson, 2002).
Multiple modes of locomotion make the Entomopter particularly well suited to operations
in varied terrain. The flight capability of the Entomopter allows for navigation through
ventilation systems, doors, or windows. Its crawling capability allows it to maneuver into spaces
where flight is not possible such as under a closed door and around large obstacles. Crawling
also uses less power than the Entomopter’s flight mode, therefore, a mission could be allowed to
continue on the ground once power for flight had been expended. The possibility of damage to
the flight system during operation would also become less of a concern because of the existence
of an alternate method of locomotion. Entomopter designs have even considered the possibility
of including a swimming form of locomotion specifically for navigating through sewers,
however the current configuration only includes the dual mode flight and crawling options
(Michelson, 2002).
Mars-based Mars Flyer Entomopter Unmanned Aerial Vehicle
Exploration of the Mars surface is an important area of space research because it may
provide greater understanding of the physical and biological histories of the planets in the solar
system, which may yield clues to the planetary evolution of planet Earth. To date, two primary

methods of planetary exploration have been employed to remotely observe Mars from Earth:
remote sensing via Mars orbiting satellite and rover data collection from the surface of the
planet. The National Aeronautics and Space Administration (NASA)’s Mars Global Surveyor
satellite was placed into orbit around Mars in 1997 and the European Space Agency’s Mars
Express satellite started orbital monitoring in 2003. These satellites provide image data of the
Mars surface from orbit using wide angle lens cameras which allow for large coverage of the
planet’s surface at the detriment of resolution (Shimoyama, 2006). More detailed imaging of
Mars has been provided through the use of surface rovers. NASA deployed rovers
“Opportunity” and “Spirit” in 2003. They have captured high resolution images which have
provided more detailed mapping of the Mars surface, but their coverage is limited to the small
area that they can traverse. The use of aircraft for Mars exploration is anticipated to be the next
step in Mars surveying due to their ability to provide high resolution remote sensing to a much
larger areas than can be explored by surface rovers (Shimoyama, 2006). While the concept of
using aircraft to observe Mars has many benefits, the reality of designing aircraft that can fly in
Mars’s atmosphere is extremely challenging using present terrestrial aircraft specifications.
The Mars environment is particularly inhospitable to aircraft that can function without
difficulty on Earth. The low density and low oxygen atmosphere of Mars creates a very similar
low Reynolds number flight environment that the terrestrial Entomopter MAV thrives in
(Michelson, 2002). The flapping wings of the Entomopter make it capable of producing high lift
while maintaining the stationary positioning of its fuselage as it moves slowly above the Mars
surface. The flight of such an aircraft would greatly increase imaging capabilities beyond what
is currently capable with surface rovers (Laan et al., 2004). Many of the flight characteristics of
the terrestrial Entomopter MAV will be used for Mars exploration, however, the physical

dimensions are being scaled up to a small-scale unmanned aerial vehicle in order to facilitate
sample collection and a greater maximum range. The proposed size increase enlarges the wing
span of the Mars Flyer Entomopter to 1 meter which would allow it to operate with a Reynolds
number comparable to that of insect flight on Earth (Michelson & Navqi, 2003). The anaerobic
propulsion system selected for the terrestrial Entomopter MAV will also be scaled up for the
Mars version as it can operate in a low oxygen environment using multiple fuel sources
including hydrazine which is currently used on spacecraft (Michelson, 2002). Current wing
design dimensions for the Mars Flyer Entomopter are shown in Table 9.
Wing Span 1 m
Aspect Ratio 5.874
Wing Area 0.546 m2
Table 9. (Michelson & Navqi, 2003, p. 8)
The NASA Institute for Advanced Concepts has outlined several possible mission
structures for the exploration of the Mars surface using the Mars Flyer Entomopter. The
dimensions of the Entomopter are limited by the payload specifications of the launch vehicle
used for both launch to Mars and by the payload specifications of the Mars lander used. The
Arianne 6 launch vehicle has been studied for compatibility with the Entomopter, and the need
for folding wings to reduce width requirements has been theorized. The specifications of the
Mars mission that will deploy and operate the Mars Entomopter are currently unknown;
therefore the design of the Entomopter configuration has been made to be adaptable to any of the
following possibilities: exploration within range of a central vehicle, independent exploration
using an Entomopter, and an Entomopter that works in tandem with a rover (Michelson, 2002).
The mission of the Entomopter operating within range of a central vehicle assumes a
Mars lander containing several Entomopters descends to the Mars surface and deploys the
vehicles. The lander is then used as a base of operations for relaying communications between

the Entomopters and Earth, refueling of Entomopters between surveying tracks, and for storage
of image data and samples collected during the course of the mission. The primary disadvantage
of the central lander scenario is that the exploration area of the Mars surface is limited to the
round trip range of the Entomopters around the fixed area of the central lander (Michelson,
2002).
The second possibility for the design of the Entomopter mission to Mars increases the
range of surface exploration to the full range of the Entomopter through independent exploration.
A lander is still used to descend to the surface of Mars and deploy the Entomopters. However,
this scenario requires that the Entomopters themselves are capable of relaying telemetry back to
Earth. The lander only serves as the initial transportation to the planet. The Entomopters for this
mission are one-way and expendable unless some way of harvesting fuel from the Mars
environment can be found. The advantage of the independent Entomopter exploration mission is
that the effective range of the Entomopters is doubled from the central lander scenario.
However, the ability to return to a previously explored area or the collection of environmental
samples is not an option (Michelson, 2002).
Lastly, the exploration of the Mars surface may be accomplished through a tandem
system in which an Entomopter operates in conjunction with a rover. A lander containing either
a single or multiple Entomopters as well as a surface rover descends to the surface of Mars. The
vehicles are deployed. The central lander operates as a vehicle transport, communications relay,
and operates as a refueling station for the rover. The rover, in turn, serves as the Entomopter’s
base of operations and transfers fuel for the course of the mission. The Entomopters relay
telemetry and communications with the rover which then relays the information to the lander.
Rover navigation is enhanced using Entomopter mapping data throughout the course of the

mission. The feasibility of this mission profile relies on several key factors. The rover itself
must be able to recharge during the mission through solar panels and battery storage. The
chemical fuel for the Entomopters must be able to be transferred from the central lander to the
rover and then stored on the rover. The principal advantage to the tandem operations scenario is
that the Entomopters can explore new terrain on a daily basis while the surface rover slowly
advances across the Mars surface (Michelson, 2002).
Low Reynolds Number Aerodynamics
The flight of birds, bats, and insects occurs in the flight regime known as low Reynolds
number flight. Out of thirteen thousand warm blooded vertebrates, ten thousand of them fly.
Insects are even smaller flyers, and there are nearly one million species of flying insects (Shyy,
2008). Aerodynamics research and aeronautical technology have advanced dramatically over the
last century, but flight performance of aircraft is still far behind nature’s flying machines which
have evolved their flight characteristics over the span of roughly one hundred and fifty million
years. The top speed of humans is about four body-lengths per second, the top speed of horses is
nearly 7 body-lengths per second, and the SR-71 Blackbird stealth aircraft manages 32 body-lengths
per second at Mach 3. It is astonishing that the common pigeon can attain speeds of
seventy-five body-lengths per second, and the European starling flies at one hundred and forty
body-lengths per second. The maneuverability and resiliency of birds in flight is also quite
amazing. The roll rate of one of the most maneuverable aerobatic aircraft, the A-4 Skyhawk, is
720º per second while the Barn Swallow has a roll rate of over 5000º per second. Military
aircraft can withstand up to ten times the gravitational force, while many birds routinely
experience up to 14 gravitational forces during flight (Shyy, 2008).

Micro aerial vehicles operate in a very sensitive flight regime due to their small size and
weight where the flight characteristics of MAVs are subject to low Reynolds number
aerodynamics. At low Reynolds numbers, lift is particularly difficult to produce across a wing as
the more the airflow separates it becomes affected by a multitude of complex flow phenomena
that are not present in the smooth flow that occurs during more traditional flight at higher
Reynolds numbers (Pines & Bohorquez, 2006). Until recently, there has been a lack of
knowledge about the fundamentals of flow aerodynamics at low Reynolds numbers. The only
flying “machines” that have been able to successfully operate at such low airflow have been
birds and insects. Accurate modelling of these natural low Reynolds number flyers has led to the
greater understanding of non-traditional lift generation, and this has allowed for the first
prototypes of small-scale mechanical flying machines to operate successfully (Pines &
Bohorquez, 2006). The necessary study of bird and insect flight aerodynamics has given rise to a
new type of flight design suitable for flight at low Reynolds numbers called biokinetic flight, as
the flight mechanisms mimic naturally occurring biological characteristics (Azuma, 2006).
The high performance, maneuverability, and structural resilience of biological flyers has
been sought after since the beginnings of flight experimentation, but these capabilities have
proven difficult to replicate by manmade flying machines (Shyy, 2008). However, recent
advancements in materials and control technologies along with a greater understanding of
biological aerodynamics have finally brought the possibility of developing aircraft which can
operate in the same flight conditions as bird and insects. Research in these MAVs in low
Reynolds number flight has given rise to greater performance and efficiency with every design
iteration.

MAV flight shares several major unique characteristics to biological flight despite
differences in flight mechanisms. See Appendix F for this comparison of characteristics in the
Great Flight Diagram. The small size of MAVs causes them to operate in low Reynolds
numbers (104-105) which leads to degraded aerodynamic performance. The overall small
dimensions and weight of MAVs result in greatly reduced payload capabilities. However, the
reduced structural dimensions also have the effect of increasing overall structural strength when
loaded, reducing stall speed, and increasing the overall impact tolerances of the aircraft (Shyy,
2008). MAVs also have a much lower flight speed due to their smaller scaling which results in
unsteady flight characteristics due to weather effects and wind gusts as well as perturbations in
the flight environment such as those caused by flow separation effects (Jacob, 2010). Efficient
operation in low Reynolds number environments requires use of nontraditional airfoil shapes
compared to the standard thicknesses, amounts of camber, and aspect ratios used in larger
manned aircraft which operate in much different flight conditions (Shyy, 2008). This is
demonstrated by the relationship between the parameters which make up the Reynolds number
which is fundamental to understanding the physical limitations of MAV flight.
The Reynolds number is a dimensionless expression of the relationship between the
variables involved with flow of a fluid over an airfoil. By definition, the Reynolds number is the
ratio of inertial forces to viscous forces on an airfoil in a fluid (Pines & Bohorquez, 2006). For
traditional, steady-state, aerodynamic conditions this ratio is given by Equation 1 where ρ is the
density of the fluid, V is the velocity of the fluid over the airfoil, μ is the viscosity of the fluid,
and c is the characteristic airfoil chord length.
푅푒 = 휌푉푐
휇
Equation 1. (Pines & Bohorquez, 2006, p. 295).

Low Reynolds number flyers are subject to aerodynamic scaling laws which relate to the
basic steady-state equation for the Reynolds number, Equation 1. The smaller in size the flyer is,
the faster it must flap its wings in order to generate enough lift to stay airborne (Shyy, 2008). A
reduction in size also causes the flyer to experience lower wing loading from the surrounding
airflow. A slower cruising speed, lower stall speed, and greater crash landing resiliency also
result from a reduction in dimensions. In turn, low Reynolds number flyers become more
susceptible to the flight environment caused by weather conditions and wind gusts, and their
steady stream flight produces a reduced lift-to-drag ratio. The complex flight dynamics of
biological flyers mitigate this lift reduction by flapping their wings in order to generate
additional lift and maneuverability in turbulent flight conditions. An overall reduction in weight
causes a decrease in the amount of “fuel” storage possible for the biological flyer and subsequent
need to refuel frequently (Shyy, 2008). The weight of fuel and power output from small
dimensioned power sources remains a significant design challenge for mechanical low Reynolds
number flyers such as MAVs.
Biological flyers such as birds and insects can generate lift forces anywhere from two to
twelve times their body weight (Pines & Bohorquez, 2006). Steady-state aerodynamics fails to
explain this large amount of lift with respect to size. Current research has been focused on
modelling the flight behavior of the most aerodynamically efficient biological flyers in wind
tunnels in order to understand the more complex aerodynamics associated with their flight. The
pervading theory that is emerging has concluded that the wing pitching/plunging/lagging motion
of birds and insects is responsible for the extreme increase lift that cannot be explained by
traditional steady-state aerodynamic theory. Biological flyers also have the ability to change
their wing shape during flight to accommodate complex flow conditions which can

instantaneously alter the aspect ratio, wing warping, and camber length in mid-flight (Pines &
Bohorquez, 2006). To date, no mechanical aircraft has had the ability to alter its wings so
fundamentally. Aircraft have had to rely on set flight mechanisms in order to achieve sustained
flight that remain the primary limitation during aerodynamic and weather related airflow
changes. MAV aircraft are no exception despite advances made in mimicking biological flight
mechanisms. MAVs have wing configurations which allow for sustained flight in low Reynolds
number environments which include fixed-rigid wing and rotary-wing conventional designs as
well as biologically mimicking flapping and flexible wing designs.
Fixed-Rigid Wing Micro Air Vehicle Performance
Fixed-rigid wing Micro Air Vehicles have designs that resemble their traditional manned
airplane counterparts, but they have been scaled down in order to meet the size requirements for
MAVs. Their aerodynamics can largely be explained by steady-state aerodynamics, but they are
extremely prone to turbulence and weather related effects due to their small size. The
performance characteristics for fixed-rigid wing MAVs are linked to their engine and
aerodynamic efficiencies just as they are in traditional aircraft. The endurance of fixed-rigid
wing MAVs at cruising speed is given by the conventional endurance equation for an aircraft in
steady-state conditions powered by an internal combustion engine where E is the endurance, η is
the propeller efficiency, 푐푓 is the specific fuel consumption of the engine, 퐶퐿 is the coefficient of
lift, 퐶퐷 is the coefficient of drag, 휌∞ is the density of the fluid (air at a given altitude for an
aircraft), S is the wing surface area, 푊푓 is the final weight of the aircraft (typically the weight of
the aircraft minus fuel consumed), and 푊0 is the initial weight of the aircraft.
퐸 = η
푐푓
3
⁄2
퐶
퐿
퐶퐷
√2휌∞푆 ( 1
√푊푓
− 1
√푊0
) Equation 2. (Pines & Bohorquez, 2006, p. 292)

Equation 2 determines the design characteristics of fixed-rigid wing MAVs that must be
taken into account in order to achieve the maximum power and efficiency possible for an MAV
during flight. The lift coefficient of the wings, propeller efficiency, and wing loading must be at
a maximum and its wing drag coefficient and operational altitude must be at a minimum to
achieve the greatest possible endurance performance for the MAV (Pines & Bohorquez, 2006).
Rotary-Wing/Vertical Take-Off and Landing Micro Air Vehicle Performance
The performance of rotary-wing/vertical take-off and landing (VTOL) vehicles is well
studied for full-scale rotorcraft under steady-state conditions, but the actual performance of
MAV rotor efficiency in hover at low Reynolds numbers is less understood. Therefore,
performance characteristics for rotorcraft MAVs rely on a comparison of design-determined
ideal power output compared to the actual power output required to maintain hovering flight
given by Equation 3 where FM is the rotor Figure of Merit, T is the thrust, υ is the rotor induced
velocity, and P is the power supplied to the rotor by the engine:
푖푑푒푎푙 푝표푤푒 푟
푎푐푡푢푎푙 푝표푤푒푟
FM=
= 푇휐
푃
Equation 3. (Pines & Bohorquez, 2006, p. 294)
The ideal rotorcraft would have a rotor that functioned without mechanical or
aerodynamic losses and have an FM of 1. However, a rotorcraft MAV functioning in actual
environmental conditions can only hope to minimize its losses while maximizing its thrust. This
will be seen by an FM as large as possible. Using the basic momentum equation, the relationship
of power loading (P.L. = Power/Thrust) to disk loading (D.L. = Thrust/Disk Area) can be derived
from the FM relationship and yields the power efficiency of hovering aircraft:
푃. 퐿. = 0.638 퐷.퐿.
퐹푀
Rotorcraft MAV designs face significant challenges when scaling a conventional rotor
configuration down to MAV size constraints. Drag losses rapidly increase at low Reynolds

numbers which greatly reduce the lift-to-drag ratios for MAV rotorcraft. The airfoil thickness of
the rotor blades increases the disk loading at smaller dimensions, therefore, conventional rotor
airfoil shapes cannot be used. Surface roughness of the rotor also plays a significant role in the
performance of MAV rotorcraft at low Reynolds numbers as it increases the overall drag on the
rotor disk (Pines & Bohorquez, 2006).
Flapping Wing Micro Air Vehicle Performance
Performance characteristics for Micro Air Vehicle wing designs that are based on
biological flight have more complex relationships than for fixed- and rotary-winged MAVs.
Elements of conventional fixed and rotary wing flight that generally contribute to an increase in
drag and subsequent decrease in efficiency during conventional flight can suddenly become
assets to more biologically adapted flapping wing flight. The current power and efficiency
equations for flapping winged MAVs have been approximated using modelling data derived
from bird and insect flight in a wind tunnel. Insect flight is particularly efficient and is
characterized by four mechanical phases: an upstroke, a downstroke, a pronated rotation, and a
supinated rotation (Pines & Bohorquez, 2006). See Appendix G for the Components of Insect
Flapping Wing Flight. Because of insect flight’s high efficiency, it has been more intensely
studied as a means of efficient flapping wing MAV flight than less efficient biological flight
mechanisms. Insect wing performance can be approximated using the mean Reynolds number
for an insect wing given by Equation 5 where Re is the mean Reynolds number, Ф is the
wingbeat amplitude from peak to peak, f is the wing-beat frequency, R is the wing length/span,
and AR is the aspect ratio of the wing:
푅푒 = 4Ф푓 푅2
휐퐴푅

Insect flight performance is remarkably efficient despite its low Reynolds number flight
environment. Insects of varying sizes fly in Reynolds number regimes between 10 and 104
(Pines and Bohorquez). For flapping wing flight, the airflow exhibits predominantly
conventional steady state aerodynamics with the benefit of several complex unsteady flight
mechanisms which improve flight performance (Pines & Bohorquez, 2006). The study of these
unsteady flight mechanisms show promise in explaining how flapping wings can generate such
large lifting forces over a complete wing flapping cycle. Under steady-state aerodynamic
conditions, a high angle of attack of a wing against the direction of airflow velocity will create an
increase in pressure near the leading edge of the airfoil, and causes flow separation and
turbulence (Pines & Bohorquez, 2006). This typically increases the overall drag on a
conventional aircraft wing. However, in the case of flapping wing flight, this flow separation is
used to increase lift. When flow separation occurs due to an increased angle of attack, a vortex
forms just in front of the wing and begins to move along the upper surface of the wing along the
path of the airflow. The force of the additional vortex induces a pressure wave which can
provide additional lift and help to produce airloads many times over those found on a
conventional rotorblade or wing in steady state flight (Pines & Bohorquez, 2006). While insect
wing beating can be related to helicopter dynamics in the upstroke and downstroke phases,
additional unsteady flight mechanisms in the remaining two rotational phases are the most likely
to provide the extremely enhanced lift seen in wind tunnel testing. The rotational phases of
insect flight involve pronation and supination of the wings which lead to an increase in lift
provided by the unsteady flight mechanisms: delayed stall due to flow separation, wake capture
which helps to generate additional power from turbulent airflow, rotational circulation which
increases lift, and bound circulation which also serves to generate additional lift (Pines &

Bohorquez, 2006). However, these crucial unsteady flight mechanisms remain little understood
by modern aerodynamics. The challenge of producing a viable flapping wing MAV relies on
further investigation of unconventional aerodynamics. Flapping wing MAVs to date have relied
on mimicking naturally occurring wing shapes and wing beating cycles as closely as possible in
an attempt to reproduce the considerable increases in aerodynamic performance attained by
insects.
Flexible Wing Micro Air Vehicle Performance
Fixed wing micro air vehicles are typically designed with conventional aircraft structures
despite their smaller scale. Ribs and spars make up the structure of the aircraft which is then
covered with a suitable skin with a low overall weight and high tensile strength and stiffness
(Pines & Bohorquez, 2006). The wings of conventional aircraft do not flap like those of
biological flyers, and conventional construction methods appear to fail to remain strong and
supple enough to withstand the comparatively large aerodynamic forces present in low Reynolds
number flapping-wing flight. Therefore, there is a considerable advantage to using flexible
wings for small-scale flight (Pines & Bohorquez, 2006).
Biological flyers depend on flexible wing structures in order to adapt to the flow
environment. Bird wings, for example, have layers of lightweight and strong feathers which
allow them to quickly adapt their wing shape for a particular flight mode. Bats have even more
complex wing structures than birds. Two dozen independently controlled joints make up each
bat wing, and their bones can withstand large amounts of deformation. They can change their
wing shapes drastically to allow them to manipulate their wing camber and create a three
dimensional wing surface to suit even the most extreme aerodynamic stresses. Bats are
extremely maneuverable and have the ability to flight in both positive and negative angles of

attack with turn rates which exceed 200º per second. Both birds and bats have the ability to
drastically change their wing shape during flight. The wing area and wing span can be quickly
decreased by flexing their wings in order to increase forward velocity or reduce drag during the
upstroke of a wing beat (Shyy, 2008). Nature’s flexible membrane wing adaptations are being
studied specifically for use in MAV design as they provide an increase in maneuverability during
flight which serves to significantly enhance MAV flight performance in the low Reynolds
number regime.
Aerodynamic performance characteristics for flexible wings are difficult to reduce to
simple mathematics, and they are more accurately determined through wind tunnel modelling
using computational fluid dynamics. However, basic structural flexibility can be taken into
account using the same aerodynamic relationships used for flapping flight in the specific case of
a flexible-wing flyer using flapping to generate lift. In order to do this the four phase flapping
wing motions are given by two linear motions: upstroke and downstroke and two rotational
motions that are corrected to take wing flexibility into account: pronation and supination (Nakata
& Liu, 2011). The rotational motions are approximated by a sine wave to describe their motion
′ and 훼푠1
during flapping-wing flight where 휑푐1
′ are rotational coefficients determined by
experimental data and ω is the angular frequency of the sine wave created by the flexibility of
the flapping wing given by:
′ cos(휔푡) Equation 6. (Nakata & Liu, 2011, p. 3)
휑 = 휑푐1
′ 푠푖푛(휔푡) Equation 7. (Nakata & Liu, 2011, p. 3)
훼 = 훼푠1
Aerodynamic performance characteristics are determined by the modified Reynolds
number for flexible wing flight in a flapping-wing configuration which is given by Equation 5,
Reynolds number for a flapping wing, where Re is the mean Reynolds number, Ф is the

wingbeat amplitude from peak to peak, f is the wingbeat frequency, R is the wing length/span,
and AR is the aspect ratio of the wing:
푅푒 = 4Ф푓 푅2
휐퐴푅
Flexible wing flight is advantageous to both natural and mechanical flyers as it allows for
increased maneuverability and resilience when handling the large aerodynamic forces inherent in
low Reynolds number flight conditions. The flexing of a wing membrane can cause an increase
in forward velocity and minimize drag on the wing. Even fixed-wings with flexible components
can benefit from the increased range of motion which results in more steady state, controlled
flight. Environmental effects such as wind gusts become less problematic for flexible wing
configurations which provide a more stable lift-to-drag ratio than seen by non-flexible rigid
wings. A membrane wing is also more responsive to variable aerodynamic loads along the wing
surface and can actively contract in order to delay stall. Membrane wings have also been found
to increase overall lift by producing flutter vibrations even in steady state conditions and for rigid
fixed-wings as well as for flapping wing (Shyy, 2008). A flexible wing structure has the
potential to greatly increase the lift and aerodynamic performance of MAVs regardless of wing
configuration because of the increases in adaptability to flight conditions which are otherwise
problematic to aircraft operating at low Reynolds numbers.
Wind Gusting and Other Meteorological Concerns
Recent advances in Micro Air Vehicle aerodynamics have yielded prototypes which are
beginning to facilitate both military and civilian mission parameters. While they are functionally
able to carry out their proposed mission capabilities, they must be robust enough to operate in
real world environments which have airflow and weather effects which are not concerns in the
steady state laboratory environment (Zarvoy & Costello, 2010). MAVs are aircraft that have

MASThesis_FutureOfMicroAerialVehicles

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