Unmanned Aircraft Systems
By Anibal Ollero and Antonios Tsourdos
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Unmanned Aircraft Systems - Ella Atkins
Contributors
Brandon R. Abel
International Center for Air Transportation, Massachusetts Institute of Technology, Cambridge, MA, USA
Domenico Accardo
University of Naples Federico II
, Napoli, Italy
José Joaquin Acevedo
Grupo de Robótica, Visión y Control, Universidad de Sevilla, Seville, Spain
Florian-Michael Adolf
German Aerospace Center (DLR), Department of Unmanned Aircraft, Institute of Flight Systems, Braunschweig, Germany
Jessica Alvarenga
Ritchie School of Engineering and Computer Science, DU Unmanned Research Institute, University of Denver, Denver, CO, USA
Brian M. Argrow
Department of Aerospace Engineering Sciences, Research and Engineering Center for Unmanned Vehicles, University of Colorado Boulder, Boulder, CO, USA
Begoña C. Arrue
Grupo de Robótica, Visión y Control, Universidad de Sevilla, Seville, Spain
Ella M. Atkins
Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA
Randal W. Beard
Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA
Yunfeng Cao
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Jesús Capitán
Grupo de Robótica, Visión y Control, Universidad de Sevilla, Seville, Spain
Philip B. Charlesworth
Airbus Group Innovations, Newport, UK
Wen-Hua Chen
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, UK
Yang Quan Chen
School of Engineering, University of California, Merced, CA, USA
Matthew Coombes
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, UK
Mary L. Cummings
Humans and Autonomy Laboratory, Duke University, Durham, NC, USA
Dan DeLaurentis
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
Pedro F.A. Di Donato
Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA and National Civil Aviation Agency–Brazil (ANAC), São, José dos Campos, Brazil
Haibin Duan
School of Automation Science and Electrical Engineering, Beihang University, Beijing, P.R. China
John T. Economou
Centre for Defence Engineering, Defence Academy of the United Kingdom, Cranfield University, Swindon, UK
Gary J. Ellingson
Mechanical Engineering Department, Brigham Young University, Provo, UT, USA
Paul G. Fahlstrom
United States Army Materiel Command, Huntsville, AL, USA
Farhan A. Faruqi
Information Processing and Human Sciences Group, Combat and Mission Systems, WCSD, Defence Science and Technology Organisation, Edinburgh, South Australia
Giancarmine Fasano
University of Naples Federico II
, Napoli, Italy
Karen Feigh
Cognitive Engineering Center, Georgia Tech, Atlanta, GA, USA
C.E. Noah
Flood
CAVU Global LLC, Purcellville, VA, USA
Michael S. Francis
United Technologies Research Center, East Hartford, CT, USA
Seng Keat Gan
Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia
Alessandro Gardi
RMIT University, Melbourne, Australia
Thomas J. Gleason
Gleason Research Associates, Inc., Columbia, MD, USA
R. John Hansman
International Center for Air Transportation, Massachusetts Institute of Technology, Cambridge, MA, USA
Inseok Hwang
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
Mario Innocenti
Munitions Directorate, Eglin Air Force Base, Air Force Research Laboratory, FL, USA
Pantelis Isaiah
Faculty of Aerospace Engineering, The Technion—Israel Institute of Technology, Haifa, Israel
Stéphane Kemkemian
Thales Airborne Systems, Elancourt, France
Seungkeun Kim
Department of Aerospace Engineering, Chungnam National University, Daejeon, Republic of Korea
Trevor Kistan
RMIT University, Melbourne, Australia and THALES Australia, Melbourne, Australia
Daniel P. Koch
Mechanical Engineering Department, Brigham Young University, Provo, UT, USA
Cheolhyeon Kwon
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
Jack W. Langelaan
Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA, USA
Nicolas Léchevin
Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Quéebec, Canada
Christopher W. Lum
William E. Boeing Department of Aeronautics & Astronautics, University of Washington, Seattle, WA, USA
Douglas M. Marshall
TrueNorth Consulting LLC, Grand Forks, ND, USAand De Paul University College of Law, Chicago, IL, USA
David W. Matolak
Department of Electrical Engineering, University of South Carolina, Columbia, SC, USA
Iván Maza
Grupo de Robótica, Visión y Control, Universidad de Sevilla, Seville, Spain
Timothy W. McLain
Mechanical Engineering Department, Brigham Young University, Provo, UT, USA
Luis Merino
Grupo de Robótica, Visión y Control, Universidad Pablo de Olavide, Seville, Spain
Antonio Moccia
University of Naples Federico II
, Napoli, Italy
Linas Mockus
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
Eric Mueller
NASA, Moffett Field, CA, USA
Myriam Nouvel
Thales Airborne Systems, Elancourt, France
Paul W. Nyholm
Mechanical Engineering Department, Brigham Young University, Provo, UT, USA
Hyondong Oh
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, UK
Aníbal Ollero
Universidad de Sevilla and Scientific Advisory Department of the Center for Advanced Aerospace Technologies, Seville, Spain
Martina Orefice
Air Transport Sustainability Department, CIRA Italian Aerospace Research Center, Capua, Italy
Charles H. Patchett
School of Engineering, University of Liverpool, Liverpool, UK
Lorenzo Pollini
Department of Information Engineering, University of Pisa, Pisa, Italy
Amy Pritchett
Cognitive Engineering Center, Georgia Tech, Atlanta, GA, USA
Camille A. Rabbath
Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Quéebec, Canada
Matthew R. Rabe
International Center for Air Transportation, Massachusetts Institute of Technology, Cambridge, MA, USA
Subramanian Ramasamy
RMIT University, Melbourne, Australia
Francisco J. Ramos
UAS Ground Segment Department, Airbus Defence & Space, Getafe, Spain
James M. Rankin
Avionics Engineering Center, School of Electrical Engineering and Computer Science, Russ College of Engineering and Technology, Ohio University, Athens, OH, USA
Keith A. Rigby
BAE Systems, Warton Aerodrome, Preston, UK
Matthew J. Rutherford
Ritchie School of Engineering and Computer Science, DU Unmanned Research Institute, University of Denver, Denver, CO, USA
Roberto Sabatini
RMIT University, Melbourne, Australia
Daniel P. Salvano
Aviation Consultant, Safety, Certification and CNS Systems, Haymarket, VA, USA
A. Savvaris
Centre for Cyberphysical Systems, Institute for Aerospace Sciences, Cranfield University, Cranfield, UK
Corey J. Schumacher
711 HPW/RH, Wright-Patterson AFB, Ohio, OH, USA
Pau Segui-Gasco
Centre for Autonomous and Cyber-Physical Systems, SATM, Cranfield University, Cranfield, UK
Madhavan Shanmugavel
School of Engineering, Monash University Malaysia, Selangor, Malaysia
Tal Shima
Faculty of Aerospace Engineering, The Technion—Israel Institute of Technology, Haifa, Israel
Hyo-Sang Shin
Centre for Autonomous and Cyber-Physical Systems, SATM, Cranfield University, Cranfield, UK
Brandon J. Stark
School of Engineering, University of California, Merced, CA, USA
Chun-Yi Su
Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Quéebec, Canada
Salah Sukkarieh
Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia
Shigeru Sunada
Department of Aerospace Engineering, Osaka Prefecture University, Osaka, Japan
Hiroshi Tokutake
Department of Aerospace Engineering, Osaka Prefecture University, Osaka, Japan
Christoph Torens
German Aerospace Center (DLR), Department of Unmanned Aircraft, Institute of Flight Systems, Braunschweig, Germany
Giulia Torrano
Air Transport Sustainability Department, CIRA Italian Aerospace Research Center, Capua, Italy
Antonios Tsourdos
School of Aerospace, Transport & Manufacturing and Centre for Autonomous and Cyber-Physical Systems, Cranfield University, Cranfield, UK
Dai A. Tsukada
William E. Boeing Department of Aeronautics & Astronautics, University of Washington, Seattle, WA, USA
Joseph J. Vacek
Department of Aviation, University of North Dakota, Grand Forks, ND, USA
Kimon P. Valavanis
Ritchie School of Engineering and Computer Science, DU Unmanned Research Institute, University of Denver, Denver, CO, USA
Antidio Viguria
Center for Advanced Aerospace Technologies (CATEC), Seville, Spain
Vittorio Di Vito
Air Transport Sustainability Department, CIRA Italian Aerospace Research Center, Capua, Italy
Nikolaos I. Vitzilaios
Ritchie School of Engineering and Computer Science, DU Unmanned Research Institute, University of Denver, Denver, CO, USA
David O. Wheeler
Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA
Brian White
Centre for Autonomous Systems and Cyber-Physical Systems, Cranfield University, Cranfield, UK
Zhe Xu
Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia
Oleg A. Yakimenko
Graduate School of Engineering and Applied Science, Naval Postgraduate School, Monterey, CA, USA
Andy Yu
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
Greg L. Zacharias
Charles River Analytics, Cambridge, MA, USA
Foreword
The Encyclopedia of Aerospace Engineering, first published in 2010, represents a singular attempt to capture the aerospace community's ever-expanding collective body of knowledge into an easy-to-use, cohesive, universal reference framework.
The past few years have marked rapid growth in aerospace systems and technology – as new and innovative designs and applications come to the fore, new ways of thinking about old challenges emerge, and as existing technology and systems have continued to evolve in new and exciting directions. This growth has been especially dynamic in the field of unmanned aircraft systems (UAS).
No longer solely the tools of the military, UAS have experienced a cost and capability revolution, performing important missions across many fields – agricultural sensing, infrastructure inspection, scientific research, and logistics – with significant implications for the research and development enterprise. The new complementary technologies involving intelligent systems are continually changing how we think about the capabilities and applications of UAS technology and how it will continue to transform our lives.
The absence of the human payload and its associated systems has inspired and delivered remarkable innovations in our industry. Yet unmanned systems still face extraordinary challenges to deliver comparable situational awareness to the operator, and we are all aware of the potential threats to safety and security associated with the widespread availability and increasing affordability of small-scale, remotely piloted aircraft. To address these challenges and to leverage these associated innovations fully, we need ongoing access to information. We therefore welcome this addition to the Encyclopedia of Aerospace Engineering as both timely and comprehensive, covering a remarkable range of UAS issues from platform technology, autonomy, security, and fail-safe systems through to integration with manned aviation and the regulatory and legal regimes – all critical pieces of knowledge if we are to continue developing the UAS enterprise to its fullest potential.
The year 2016 marks both the 150th anniversary of the Royal Aeronautical Society (RAeS) and the 85th anniversary of the American Institute of Aeronautics and Astronautics (AIAA). With a combined membership of more than 50,000 aerospace professionals, our two organizations celebrate these milestones and our members' never-ending quest for knowledge and solutions not just to the problems and challenges of today but also of the next impossible thing. It is our members who evolve UAS technology to even greater capabilities and uses than that exist today.
Aerospace make the world safer, more connected, more accessible, and more prosperous. We hope that the addition of this volume to the Encyclopedia continues this trend and is as professionally valuable and influential to its readers – and the industry – as were the preceding volumes.
As we write, there is perhaps no issue more timely in aviation than unmanned aircraft systems. That is why it is our pleasure to jointly commend to you this new contribution to the aerospace engineering body of knowledge.
Mr. James Maser
President, American Institute of Aeronautics and Astronautics
and
Vice President, Operations Program Management,
Pratt & Whitney, East Hartford, CT, USA
and
Dr. Chris Atkin
President, Royal Aeronautical Society
and
Professor of Aeronautical Engineering,
City University London, UK
Preface
The Wiley Encyclopedia of Aerospace Engineering offers the aerospace and robotics communities a series of accessible chapters covering all disciplines of the Aerospace field. While the Encyclopedia is regularly updated to ensure currency, the editors also decided to pursue new key volumes in important and emerging Aerospace areas. This volume covers the technology, operations, and policy challenges associated with both small and large unmanned aircraft systems (UAS).
Small UAS operating at low altitudes are rapidly proliferating for uses ranging from hobby to surveillance and package delivery. Configurations range from traditional fixed-wing aircraft to the popular multirotor helicopter or multicopter offering unprecedented maneuverability. Plastic and composite materials, low-cost manufacturing processes, and capable embedded sensors and processors support both the fully piloted and fully autonomous flight. Motors powered by lithium–polymer batteries are mass-produced at low cost, yet further improvements in onboard energy storage and power requirements are essential to increase small UAS range and endurance. This UAS volume provides essential background in UAS configurations and subsystem design with respect to aerodynamic, structural, propulsion, and power system considerations as well as avionics, communication, sensing, control, and planning functions.
Because traditional manned aircraft have always relied upon the onboard pilot or crew to assimilate information and make safety-critical decisions, UAS necessarily introduce a number of new challenges in control, communication, and information management. What sensing and control strategies are effective for the spectrum of UAS configurations and missions, and what level of decisional autonomy is required or even desired? How do remote operators maintain situational awareness, how can the ground–air link be ensured secure and reliable, and what protocols are appropriate in lost link situations? How will UAS sense and avoid each other and manned aircraft? What functions should be implemented onboard and which in the ground station? Small UAS may be beneficially organized in multiagent teams to simplify mission coordination and handling in the National Airspace System (NAS), the National Air Traffic Services (NATS), and other air traffic control systems. The chapters in this volume covers the spectrum of sensors, guidance, navigation, and control algorithms, and mission-level decision-making algorithms offering UAS the ability to autonomously execute mission plans and effectively coordinate actions with other UAS. Remaining challenges in ensuring secure, safe, reliable, and robust UAS operation are also discussed.
The number of UAS operations per day is expected to quickly exceed the number of manned operations. Furthermore, these operations will routinely occupy the low-altitude airspace not commonly used for manned aircraft today. Small maneuverable UAS can be launched and recovered from almost any site and flown in cluttered areas. These factors introduce a variety of new concerns related to airspace access and policy, privacy, and social/legal issues. What restrictions should be placed on UAS operations based on overflown rural to urban property as well as airspace class? How can policy and law balance the desire to capitalize on new UAS capabilities while respecting privacy concerns and ensure acceptable levels of risk exposure to overflown people and property? This UAS volume offers chapters on UAS airspace access requirements and associated policy issues. These chapters outline capabilities and needs for standards and processes enabling UAS safety certification and security. As camera-equipped UAS operate just over our backyards,
new privacy and airspace ownership and control issues have emerged that are still under discussion. Chapters in this volume also outline privacy, social, and legal issues in the context of legal precedent and emerging community concerns.
As is evident from the diverse technology, operations, and policy content in this volume, UAS are truly multidisciplinary systems
that offer exciting new mission capabilities but that also challenge traditional aviation assumptions regarding operational norms and personnel roles. UAS are motivating us to rethink information handling while truly offering everyone low-cost access to the sky.
Ella Atkins
Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA
Aníbal Ollero
Universidad de Sevilla and Scientific Advisory Department of the Center for Advanced Aerospace Technologies, Seville, Spain
Antonios Tsourdos
School of Aerospace, Transport & Manufacturing and Centre for Autonomous and Cyber-Physical Systems, Cranfield University, Cranfield, UK
Part 1
Introductory
Chapter 1
UAS Uses, Capabilities, Grand Challenges
Michael S. Francis
United Technologies Research Center, East Hartford, CT, USA
1 Introduction
2 Uses – Missions and Applications
3 Emerging Capabilities and a Look Ahead
4 Grand Challenges Ahead
5 Summary
References
1 Introduction
Unmanned aircraft have existed for almost as long as the human quest to achieve manned flight. Early unmanned heavier-than-air gliders, built by such notables as George Cayley and Otto Lilienthal, were used to pioneer the technologies required of early manned aircraft. With the powered variants that followed, the twentieth century is littered with a rich history of unmanned aircraft that were created to support an ever-increasing number of missions and applications, many driven by military needs and opportunities (Holder, 2001; Keane and Carr, 2013; Newcome, 2004). The last several decades have witnessed an even more explosive increase in unmanned aircraft of all shapes and sizes, including an increasingly large number intended for civil and commercial applications. Despite this long history, the unmanned aircraft revolution is arguably still in its infancy. To better understand this assertion, it is helpful to review the technological origins of these systems.
The technological roots of the heavier-than-air, manned aircraft are firmly implanted in the industrial age. But these machines evolved considerably over their first century of existence due, in part, to the infusion of technologies that would eventually underpin the information age. Electronics, solid state devices, microprocessors, data storage, and sensors of many types would find their way into aviation systems at virtually all levels of system architecture and operation. Later, the advent of digital communications technology and introduction of the satellite-based global positioning system (GPS) added vital elements that would further enable practical, low-cost, remote operation of these platforms.
The dramatic increases in information technology over the last several decades, coupled with concomitant decreases in the size and cost of enabling electronics, would help usher in the era of affordable unmanned air systems, or UAS, that we know today. The levels of innovation and discovery that have spurred recent growth in UAS capabilities can be expected to continue. With no abatement to Moore's law in sight and new fundamental advances such as quantum computing forecast for the not-too-distant future, the information revolution is showing few signs of slowing down. From a technology perspective, UAS can be viewed as a bellwether marriage
of the industrial age and the information revolution.
Despite the push from this high-power technology engine
and the enthusiasm of its many proponents, UAS capability has not yet seen widespread acceptance and adoption, tempered by a number of factors that can be associated with societal inertia.
These include cultural and regulatory inhibitions, legal precedents, and infrastructure constraints. And while these factors have impacted other industries and markets, their effects appear to be especially prominent for this disruptive entrant to the aviation arena.
2 Uses – Missions and Applications
2.1 Early evolution
It is not surprising that development progress in unmanned aircraft was slow during the first half of the twentieth century when the technology of electronics was in its infancy and modern digital systems were essentially nonexistent. Their early operational adaptation significantly lagged that of their manned counterparts. The first entrants were experimental and supported high-risk research and development activities aimed primarily at establishing the feasibility of manned flight. The first unmanned operational designs were intended for military applications, serving as aerial targets or actual weapons.
Perhaps the first invention to have major impact on the viability of unmanned aircraft was the multi-axis gyroscope, introduced by Elmer Sperry almost a decade after the Wright brothers first flew. Sperry's invention has been cited by some as the single most significant enabler for unmanned aviation as we know it today (Newcome, 2004). Despite this important advance, early unmanned aircraft lacked the level of navigational precision necessary to reliably accomplish military objectives. Perhaps the greatest limitation for these early systems was the lack of intelligence
required to accomplish complex missions in challenging and uncertain combat environments. Not only did these vehicles lack an onboard pilot, but also the technologies necessary for providing access to adequate remote intelligence (operators) did not yet exist. As a result, the operational footprint remained limited, with a focus largely on launch-and-leave concepts that were best suited to weapons and other expendable system applications. The Kettering Bug
and Sperry–Curtiss aerial torpedo (circa 1916–1917) and the World War II vintage German V1 buzz bomb
are examples of this trend from different eras. Over much of the twentieth century, unmanned platforms continued to serve in these roles, as end-of-life aircraft were converted to aerial targets, and high-tech cruise missile designs further expanded the arsenal of expendable, one-way platforms. It was much later that the term unmanned air vehicle, or UAV for short, would be employed to differentiate the reusable platforms from the expendable variants.
The first widespread use of reusable unmanned aircraft in an operational environment came during the course of the Vietnam War. The Ryan Firebee, originally developed for aerial target applications, was adapted to serve as an information-gathering platform in what we would call today an intelligence, surveillance, and reconnaissance – or ISR role. Launched from a large mother ship, often a C-130 transport, the Ryan AQM-34 Lightning Bug
was configured to perform a preprogrammed mission over a scripted route followed by a parachute recovery into friendly territory. It was a true unmanned air system, by today's definition (Keane and Carr, 2013). In contrast to the high-speed, turbojet-powered Firebees developed in the United States, the Israelis introduced the first low-speed, real-time surveillance UAVs during the 1973 Yom Kippur war. In both cases, these systems were introduced to achieve specific tactical objectives and retained during the conflict solely for those purposes.
Radio frequency communications technology necessary to achieve remote unmanned aircraft operation was explored and tested as early as the eve of World War I, but deemed impractical. The idea was reintroduced on the eve of World War II with some success. But the concept of remotely operated drones,
as they had then come to be called, never found a niche for a role in the broader conflict. It was a subsequent key technology development, the introduction of inexpensive solid-state radios in the 1950s that kick started
the era of modern radio-controlled aircraft in the United States. Now familiar to present day hobbyists, this was also the first introduction of remotely operated aircraft technology to a larger nonmilitary marketplace.
It was not until the introduction of modern, compact, high-performance computer technology that the contemporary UAV became attractive enough to its user community to earn a permanent place in the defense inventory. In the 1980s, the Defense Advanced Research Projects Agency, or DARPA, began developing a new class of low-cost, long-endurance unmanned aircraft that could be employed in a variety of ISR missions. The agency's preoccupation with information technology and its role in the broader information revolution at that time helped motivate adoption of the UAV as an ideal test case.
As these systems matured and gained recognition, they were embraced by a variety of government customers including the intelligence agencies and the military departments.
2.2 Dull, Dirty, and Dangerous
The first Gulf War provided the first large-scale operational opportunity to test unmanned air systems in a realistic military environment. A number of them, such as the Predator medium-altitude long-endurance (MALE) UAV, gained notoriety for their ability to provide persistent, real-time streaming video imagery to remote operational command posts, including the Pentagon, during the actual course of operations. At the time, this capability was viewed as a game changer in modern warfare.
UAVs in a variety of sizes with similar capabilities emerged to support the allied war-fighting enterprise at virtually all levels of command. From the portable, hand-launched, locally controlled Raven peeking over-the-hill for a small Marine Corps squad to the medium-altitude, wide area-surveillance Predator – operated remotely by a continental US-based ground crew, these systems gained broad acceptance by their user communities. These systems have been proliferated in large numbers as a result of the conflicts in Iraq and Afghanistan. The introduction of the even more capable Global Hawk increased operational altitudes to beyond 60 000 ft and endurance timelines to in excess of 24 h. A variety of intermediate-sized unmanned aircraft such as the Shadow and Scan Eagle Tactical UAVs, among others, were also introduced to further expand battlefield ISR to other echelons of command to a level never before seen in combat.
The Reaper, a weaponized variant of the Predator UAV, provided a unique capability never before seen in armed conflict. Combining persistent surveillance and precision targeting with near instantaneous lethal response, these platforms served as ultimate standoff snipers,
demonstrating an unprecedented level of precision engagement coupled with minimal collateral damage. Despite these unique capabilities, combat UAS have struggled to gain acceptance across the broader military community.
2.3 Emergence of Civil and Commercial Applications
Arguably, the first highly visible civil (government-sponsored, nonmilitary) applications of modern UAS were in the pursuit of scientific understanding. In the mid-to-late 1990s, the US National Aeronautics and Space Administration (NASA) funded a number of then fledgling UAS developers to demonstrate very high altitude, long-endurance civil UAS under its Environmental Research and Sensor Technology (ERAST) program. ERAST was focused on developing capabilities for probing the upper atmosphere and providing the opportunity for in-situ measurements and remote-sensing resolution that space-based sensors could not achieve. Aircraft such as Aurora Flight Sciences' Pegasus and Aerovironment's pioneering solar-powered HELIOS, among others, were developed and flown as part of that effort. In recent years, UAS have also been employed for studying a variety of atmospheric phenomena ranging from hurricanes to super cell thunderstorms and incipient tornadoes (Figures 1 and 2) (Elston et al., 2011).
Figure 1. HELIOS unmanned air vehicle.
Figure 2. Operational architecture for tornadic supercell region penetration and assessment during Vortex II campaign. (Reproduced with permission from Wiley, 2011. © Wiley.) (Courtesy J. Elston and B. Argrow, University of Colorado.)
While UAS have become a staple in modern warfare, their application to nonmilitary missions has risen dramatically in just the past few years. And despite the rich operational history of several now well-known UAS models over the past two decades of conflict, it is a new generation of platforms and technology that have captured the public's attention and interest.
Attempts to develop the so-called micro air vehicle (McMichael and Francis, 1997) reach back to the mid-1990s. But the recent, rapid ascendance and public embrace of these systems has been facilitated by the emergence of a number of new key technology elements that do not have their roots in defense technology. These include:
small, inexpensive, inherently stable, operator-friendly quad-rotor
air vehicles;
low cost, compact imaging video sensors; and
low cost, portable control stations equipped with digital wireless radio connectivity and intuitive digital operator interface.
These small and compact systems have underpinned the explosion in interest in UAS applications. The inherent stability and straightforward control of the signature multirotor platforms enable novice operators to easily control or manage their aircraft trajectories within line of sight. Public interest in social media, coupled with the fascination for flight and the low-cost entry to own and operate these systems have put them in high demand for commercial and recreational users. From realtors trying to carve out a new approach to selling property to infrastructure managers wanting to inspect otherwise inaccessible areas to a host of video enthusiasts simply trying to capture a new perspective,
small UAS have created both interest and controversy across the public domain. But while the small, easy-to-operate low-end platforms have played a significant role in increasing public interest in UAS, they do not possess the range, endurance, speed, or payload capacity of their larger, fixed-wing counterparts. A diverse array of these larger vehicles stands ready to further expand the spectrum of mission and applications.
In a recent publication addressing the civil and commercial marketplace, the Association of Unmanned Vehicle Systems International (AUVSI) highlighted a diverse range of applications; encompassing wildfire mapping; agricultural monitoring; disaster management; telecommunications; thermal infrared power line surveys; law enforcement; weather monitoring; aerial imaging/mapping; television news coverage; sporting events; moviemaking; environmental monitoring; oil and gas exploration; and freight transport (Jenkins and Vasigh, 2013). That report also predicts precision agriculture and public safety to be the two most impactful areas of commercial/civil use in the United States over the coming decade. Many of these projected applications exploit the remote sensing legacy of contemporary UAS, so successfully demonstrated by earlier military systems. This array of ISR-like applications has also been energized by the proliferation of very low cost, miniature commercial imaging sensors that have flooded the cell phone and tablet computer markets. But UAS can also be expected to be employed in an array of other uses, including the transport of cargo as an example.
Like the sensor–shooter combination demonstrated by the Reaper UAS, the on-platform integration of sensors with other payload elements affords an opportunity for further expansion of missions and applications. As an example, the combination of multispectral imaging with real-time nutrient/pesticide dispensing can potentially take precision agriculture
to another level. Similarly, real-time infrared imaging with concurrent fire suppressant application could greatly improve the ability to mitigate incipient wildfires. Although the remote sensing capability adds great value by itself, the ability to integrate it with a timely response/action mechanism greatly increases the utility of the resultant system and a host of its applications.
3 Emerging Capabilities and a Look Ahead
Today's UAS, even the small inexpensive variety, possess attributes that would be the envy of their early radio-controlled predecessors. New capabilities that improve operational versatility seem to emerge on a regular basis. Auto takeoff, auto-land, and waypoint navigation, coupled with highly stable and controllable air vehicle designs, are now commonplace even in the emerging commercial marketplace.
And while information age by-products have added significant new enabling capabilities, they have also spurred new developments on the industrial age side of the equation. For example, the search for more effective and efficient propulsion methodologies, new structural constructs, and new materials may be more extensively exploited in the unmanned systems community than the traditional manned aircraft segment.
3.1 Expanding the Design Space and Operational Envelope
The elimination of human presence on board the air vehicle affords an opportunity to introduce new attributes and mission capabilities to the aircraft, and, to some extent, redefine flight as we know it. To better understand this opportunity, it is useful to examine the benefits and constraints of the traditional onboard human presence (pilot, crew, and passengers).
In the early days of manned flight, the pilot performed all the functions necessary to control and manage the aircraft. The achievement of meaningful mission objectives under complex circumstances without the aid of an onboard human was virtually unfathomable. The pilot's eyes and ears were primary sensors, hands and feet served as primary effectors, and the human brain was the integrated flight and mission computer responsible for everything from basic maneuver execution to comprehensive mission management. In addition to direct sensing, the pilot was responsible for data interpretation and information synthesis related to all aspects of aircraft operation. Today, many of these requirements are allocated to automated systems, allowing the pilot and crew to focus on top-level supervisory tasks.
In contrast, the accommodation of human presence on board the aircraft has proven an ever more daunting and resource consuming task, as aircraft operate in domains far more demanding and complex compared to that experienced by the early aviation pioneers. The addition of pressurized systems with oxygen has become indispensable for high-altitude long-range operations. Other constraints imposed by the human anatomy have limited the way flight is prosecuted (e.g., coordinated bank to turn) and has significant impact in the design and configuration of the aircraft. The need for specific orientation with respect to the gravity vector has limited the way vertical takeoff or landing (VTOL) flight is achieved and has significant impact on the design of those aircraft.
Onboard human presence impacts flight vehicle design in many ways. It constrains platform acceleration in all axes, and limits vehicle endurance. The human factor has impacted the approach to reliability and safety from both design and operational perspectives. The need to maintain human functionality and performance within the volume and weight constrained confines of the cockpit has necessitated extensive and often costly training and proficiency regimens for the aircrew community. Onboard human presence has also invoked the addition of unique infrastructure, and diversely ranging from specialized training simulators to search, rescue, and other support capabilities that come into play in the event of aircraft mishaps. The on-aircraft interface between human and machine has become quite complex, encompassing everything from integrated control effectors, and complex displays to power-consuming environmental systems that enable crew comfort and survival during flight at all achievable altitudes and airspeeds.
While today's unmanned aircraft take full advantage of their capability for remote operation, few designs fully exploit the absence of human presence. This potential to enlarge the air vehicle design and operational envelopes is significant. A number of attributes that could be more fully advantaged in that regard include the following:
Extreme Endurance: This ability of a platform to stay aloft for periods that well exceed normal crew limitations has been demonstrated to a large extent in current operational systems. The attribute is a key performance driver for ISR mission systems such as those depicted here. 24-h endurance capabilities are commonplace for larger platforms and are rapidly becoming possible for their smaller, tactical-size counterparts. Designers are currently focused on week-long operation, with some experimental systems attempting even longer durations. Future missions such as aerial cell-phone relay and Internet distribution platforms will benefit greatly from these capabilities (Figure 3).
Small Size/Scale: The ability to build and operate aircraft incapable of physically accommodating an adult human presence has already been realized. Small UAS (sUAS), such as the AAI Shadow UAS, have proliferated in military missions for over a decade and performed admirably in a variety of tactical roles. They are enablers for a variety of civil and commercial applications ranging from highway/bridge infrastructure inspection to precision agriculture. Even smaller variants, so-called micro air vehicles
have begun to appear in real operational roles, although the very smallest, such as the Aerovironment Hummingbird is still in the experimental stage. With linear dimensions not exceeding 15 cm in any axis, they may prove extremely useful in highly confined spaces, such as building or even pipe interiors. With further miniaturization, they may even prove useful in internal bio-medical applications – exploring the interior of the human anatomy (Figure 4).
Extreme Maneuvering Capability: Unmanned platforms are, in principal, capable of sustaining accelerations and forces limited only by structural considerations, operating well beyond the tolerance of any human pilot. Turning accelerations up to approximately 30 g's – the limit where modern turbojet engines begin to experience out-of-round
geometric distortion, might be possible without the introduction of other new technology. Such capabilities could revolutionize modern air combat, even with the introduction of more agile air-to-air weapons. Structural morphing capability, such as that depicted in this DARPA concept could be exploited to increase maneuver accelerations in future unmanned combat aircraft (Figure 5).
Arbitrary Orientation: Unlike manned aircraft, the physical orientation of an unmanned air vehicle in any phase of flight need never be dictated by human physiology limitations. In theory, it can be completely arbitrary, limited only by physics-of-flight considerations and mission needs. An example illustrating the potential utility of this attribute is found in the tail-sitter concept, whose roots go back to the early 1950s in a then-impractical manned design (Chana and Coleman, 1996; Taylor and Michael, 1977). A modern UAS variant (the Sikorsky VTOL X-Plane) is an aircraft designed to pioneer the prospect of runway independent launch and recovery while achieving fixed wing-competitive cruise speeds. This class of aircraft has the potential to revolutionize high-priority transport – enabling, for example, the retrieval of cargo from a ship at sea and its rapid transport to even remote, unimproved areas without the need for a runway or any other form of terrestrial transportation in the process (Figure 6).
Unique Configurations: Unmanned aircraft designers have already provided numerous examples of unconventional configurations ill suited to manned flight. Contemporary vehicle control technology has enabled innovative designs that capture the best of fixed and rotary wing designs in a relatively simple mechanical package. The lack of need for a conventional cockpit coupled with other attributes mentioned above can result in novel shapes and configurations more germane to niche missions or unique flight environments. Examples of these include the 1998-vintage Cypher UAV and an as yet untested dual-free wing concept capable of morphing from the biplane configuration (shown), operating at near zero-speed hover conditions, to a tandem-winged, tailless orientation that could fly at extremely high speeds because of its low aerodynamic drag (Figure 7).
Unconventional Launch and Recovery: Novel approaches for launching and recovering UAS have increased significantly, especially for smaller air vehicles. Assisted rail launch capability and net or tether recovery techniques are employed on operational aircraft such as the Insitu Scan Eagle. Larger systems may find similar opportunities as in the depicted shipboard concept where a high-performance, unmanned UCAV is tube-launched like a cruise missile and later recovered shipside, following a near vertical, high angle-of-attack approach. An articulating, conforming porous arresting structure is configured to match the aircraft's approach orientation. The concept eliminates the need for conventional, often heavy landing gear, improving the vehicle's range-payload performance. More broadly, the concept reduces the need for conventional aircraft carrier operations, while simultaneously providing airpower projection capabilities to other surface ship types. Future novel launch and recovery techniques may well enable UAS operations in otherwise impractical civil and commercial environments as well (Figure 8).
Attritability: The notion of an attritable
(limited life, yet reusable) vehicle design is unrealistic for manned aircraft, but the capability could become a practical option for a number of unmanned vehicle applications. This airplane equivalent of a reusable but otherwise throwaway styrofoam cup could fill a gap between the long-life, fatigue-limited manned aircraft designs and the single-use missile/projectile configurations in common use today. The very first DARPA UCAV platform concept depicted here invoked that capability. During peacetime, manned combat aircraft can spend in excess of 90% of their flight hours for aircrew training and proficiency. For UAS, there is no seat-of-the-pants
benefit to flying these aircraft during training missions unless operational synergies with close proximity manned aircraft are also sought. For all applications that require highly intermittent flight operations or those that involve lengthy downtime periods, limited life aircraft designs could offer significant lifecycle cost advantages. Missions such as in situ sensing of toxic or radiation clouds, where the vehicle may have to be disposed following a mission, as well as other missions into dangerous environmental conditions, such as extreme weather or other threats may be ideal for attritable aircraft. However, cost savings derived from attritable designs are likely limited, since these aircraft must possess the necessary levels of safety and reliability to conduct missions in shared common airspace (Figure 9).
Figure 3. Long-endurance aircraft examples.
Figure 4. Small UAVs. (Courtesy AeroVironment, Inc.)
Figure 5. Extreme maneuvering may be enabled by morphing structure. (Reprinted with permission from Defense Advanced Research Projects Agency. Approved for Public Release, distribution unlimited.)
Figure 6. Arbitrary orientation – example: the Sikorsky VTOL X-Plane Concept. (Reproduced with permission from Chris VanBuiten, 2016. © Sikorsky Innovations.)
Figure 7. Unique configurations.
Figure 8. Novel shipboard launch and recovery of high-performance UAV.
Figure 9. Attritable
aircraft concept icon – DARPA's Unmanned Tactical Aircraft.
3.2 Autonomy
Automation has already contributed to a number of operational improvements for UAS by providing more time flexibility for the remote human crew to assess and act on information as the mission unfolds. The continued advance of modern computing power is opening the door to even higher levels of autonomous operation, where the human element is fully relieved of many minor decisions and becomes essentially supervisory in nature.
Fully autonomous flight remains an elusive objective for UAS proponents and will likely remain so for the foreseeable future. The leap from today's automation to tomorrow's autonomy is not a small step. An automated system is constrained to operate within prespecified bounds, with anticipated and preprogrammed alternatives available in the event of non-nominal circumstances. Most automation today is centered on basic, prescriptive flight functions, such as, for example, vehicle control (e.g., fly-by-wire control) or navigational route execution (so-called waypoint navigation). These advances have greatly improved the ability for the remote crew to interact intermittently in controlling the aircraft. However, much remains to be done in this domain. For example, many systems today limit UAS operation to one vehicle by one operator. Studies have been conducted to illustrate the possibility of managing multiple aircraft with a single human operator, if the level of supervisory interaction is high enough (Ruff, Narayanan, and Draper, 2002). For the latter to occur, the level of autonomy at the vehicle and system levels must increase dramatically.
Increasing the level of autonomy of an unmanned air system requires more than adding functionality in the form of new tasks or increasing task levels. A truly autonomous system would be capable of identifying and assessing a broad range of mission-level conditions and then adapting, as needed, to accomplish necessary tasks as the mission unfolds. It would be capable of brokering solutions that account for multiple objectives and circumstances that may have impact on the aircraft in its mission over several time scales (epochs) simultaneously. For example, an aircraft may be faced with a short-term requirement to avoid an unexpected obstacle, while coping with a potential threat just over the horizon, and while also facing a change to its overall mission endgame objective. A capable autonomous mission manager must cope with all of these circumstances simultaneously, while projecting an acceptable solution and executing successful outcomes throughout the mission timeline. The system would be capable of dealing with a broad range of variables, ranging from traditional well-defined physical parameters to less objective conditions, such as evolving environmental changes or even less predictable threats, such as those imposed by a human adversary.
The metric that best separates an autonomous system from a highly automated one is the ability to cope with the unknown – the condition or situation which was not considered in the system's in-the-box
design. The ability to manage these kinds of contingencies will define the level of autonomy in future UAS. These future autonomous systems must be capable of learning from their experience, for it is that trait and the ability to adapt as a result that enables this behavior in the first place. Coping with the statistical probabilities associated with the operational environment, and adapting to conditions in a manner that will improve performance, mission success, safety, or other desired objectives are key behaviors that the autonomous system must master.
Robotics and artificial intelligence remain hot topics with seemingly limitless applications – from biomedical devices to driverless cars and unmanned air systems to domestic robots that can do the family laundry. Many of the challenges associated with advancing this disciplinary arena for the broader robotics community are well documented (Hager et al., 2015).
4 Grand Challenges Ahead
Despite the tremendous potential of unmanned air systems across a range of economically beneficial and compelling applications, the obstacles to their successful introduction and implementation are significant. UAS today face a number of constraints that technology alone cannot overcome. Many are rooted in competing legacy systems and methods, as well as in institutional, regulatory, and cultural precedents that minimally assure a lengthy transition to an acceptable, productive future state. As a result, economic limitations for these systems are no longer centered on the cost of hardware and software. The fundamental inhibitions to ownership and operation can be found in the lack of acceptable regulatory infrastructure to guide their operations, combined with institutional conservatism in dealing with companion liability, insurability, legal issues, along with the concomitant consequences of negative public perceptions.
The Grand Challenges
are those that require a coordinated, integrated approach to collectively address all these issues, technical and otherwise, in a manner that will enable UAS of all types to reach their full potential.
4.1 Access to the Airspace
Today, limited access to the airspace is the dominant barrier to the realization of the full economic potential that can be derived from UAS capabilities. Most of today's operational requirements that regulate UAS operations in the common airspace are rooted in the regulatory precedents set by and for manned systems over decades with an evolved operational paradigm centered on pilot capabilities and behavior. In the manned aircraft, the pilot is omnipresent – assumed able to assess in-flight circumstances from a cockpit perspective and react to them virtually instantaneously. This is not the case with the modern UAS.
An array of real-world constraints and limitations is responsible for this dichotomy. These include wireless connectivity issues, including communications latency; environmental factors; and human frailties that can become exaggerated in the quest to provide the continuous human presence. The latter set ranges from situation awareness limitations imposed by the finite number and types of sensor and information sources to fundamental limits to human attention spans. More subtle factors associated with human cognition may also play a role. These constraints can be less significant in some operational circumstances, for example, short-duration flights within visual line of sight between the aircraft operator in reasonably good weather conditions. The problem can become acute in long-range beyond-line-of-sight operations, especially in adverse weather and/or in airspace crowded by aircraft or other physical obstacles. The need for UAS to project a continuous crew presence
– able to respond with no delay, replete with a fault-free wireless connection between platform and remote crew simultaneously – represents its most demanding requirement and its greatest vulnerability.
In keeping with the slow evolution of manned flight prevalent over the last half-century, these rules have been slow to change despite the emergence of new or improved technologies designed to enhance reliability and safety. To the impatient drone entrepreneur, progress in integrating these systems into the common airspace appears glacial across much of the breadth of the international landscape.
Larger UAS must compete to share already crowded airspace with the manned platforms that have set the precedent and expectations for flight safety. Small UAS, in contrast, are pioneering access to a new region of airspace largely unfamiliar to both pilots and regulators. This low-altitude, obstacle-rich environment, ranging from below approximately 150 m down to the blades of grass
adjacent to the earth's surface, presents a variety of challenges to remote operations. These include people – often transiting near vehicle flight routes, personal property adjacent to and along those routes, and other hazards, including nearby trees, buildings, and other obstacles.
The most difficult situations will likely involve operations in urban canyons, where traditional navigation sources like GPS are intermittent or unavailable. The most demanding of these environments have rarely, if ever been encountered by larger manned aircraft. They present a new set of challenges for the regulatory communities and the public, as well. Ironically, it is this most complex set of environments that the smallest, least capable platforms and systems (size, weight, and power) have chosen to invade.
4.2 The Quest for Trust
The arguably greatest challenge and impediment to UAS acceptance and mission proliferation lies in gaining trust in the behavior of these technologically advanced systems. This need extends to the manned aircraft-dominated user community, an outdated and often incompatible regulatory system needed to support and promote their operation, and most importantly, a skeptical public.
Although UAS technologies have made significant strides over the past several decades, their vulnerabilities are well known to most. A century of manned aviation evolution has set high expectations for safety and reliability yet to be matched by the unmanned community. Growing prospects for cyber-physical security threats in recent years have added to public skepticism. Along with growing concerns over the illicit use of UAS and their prospects for violating individual privacy, resistance to their broad introduction has been significant (Tam, 2011; Watts, Ambrosia, and Hinkley, 2012). Many of these concerns are directed at the system users, and especially at their intent and integrity. They are likely to be resolved through a combination of properly defined regulatory constraints, coupled with adequate education of potential users and the public as well.
A more immediate concern that has long-term implications over the continued evolution of UAS revolves around the issue of trust in intelligent software. This turns out to be a problem for manned and unmanned systems alike. And it has its roots in a long evolved methodology for developing trust in physical systems.
Traditional rigorous hard science-based evaluation methods created to assure developer, user, and even public confidence in engineering products such as airplanes are not likely to prove adequate for the certification of future intelligent unmanned air systems. And software is the culprit. As software-based approaches and processes have proliferated within the aviation ecosystem, their collective verification, validation, and certification (VV&C) has proven to be perhaps the most significant factor to date to impact aircraft affordability. Current VV&C techniques based on, for example, FAA-referenced DO-178 B/C and comparable standards continue to consume an ever-increasing proportion of aircraft development budgets. Prospects for their application to future advanced unmanned air systems could prove even less successful.
The incompatibility of today's software and systems VV&C regulations with future, more fully autonomous systems represents a major obstacle to the advance toward more capable UAS. As is the case with hardware, software verification and validation techniques rest heavily on a testing philosophy that is comprehensive and a companion methodology that is thorough. In hardware, scientific laws and principles underpinned by years of research have been used to derive the transfer functions that relate input stimuli to quantifiable output expectations, with predictable error limits. This is not the case for software. The substitute for the elusive transfer function has been exhaustive testing of every logic path that exists within the man-made code. As software has become more capable and complex, this testing process has become more imposing and costly, in many cases pressing on the limits of system affordability. The basic construct, which served so well in gaining engineering confidence in the early days of software definition and development, has become a significant burden in the near-explosive advance of the information revolution.
The software test philosophy has affected all current generation aeronautical systems, due to the sheer complexity associated with the large number of system interactions that the software must reflect. Recently, suggestions to redefine the verification and validation (V&V) processes based on methodologies that rely on model-based design and formal methods have provided some near-term hope for reductions in testing. But these tools today have limited to no utility and supporting the development of intelligent software.
The intelligent software that will enable true autonomous functionality will be capable of adaptation to emerging mission and environmental conditions, potentially exhibiting attributes such as emergent behavior and other nondeterministic features. These are systems capable of learning in the course of operations and applying that knowledge to future situations. Current bottoms-up methods for software evaluation based on or that assume inherent determinism are incompatible with these intelligent systems. The fundamental issue that must be resolved is not only related to the current approach to VV&C, but also to the very attributes and characteristics that must define the intelligent software itself.
It is interesting to contrast the methodology employed to develop trust in human-authored software (today's VV&C procedures) with the seemingly much simpler and quite different process used to certify true human software, that is, the pilot. That latter interaction between pilot and examiner is usually a relatively brief encounter, involves mostly high-level logic associated with complex mission-based scenarios, invokes the desire for flexible, acceptable outcomes, and takes place in the domain language of flight, as opposed to some foreign language (i.e., software code) unfamiliar to the principals. The dialog between student and certifier is less about precision than it is about decisions and judgment. And it explores the learning acquired by the student as the mission unfolds, along with the behavior it evokes. Future intelligent software may need to possess some of the same traits to permit a very different approach to VV&C from what we know it to be today.
4.3 Integration
Ultimately, the development of a methodology that addresses the certification of and trust in an integrated man–machine system, where both elements are considered together in achieving acceptable operational results, is essential. The traditional methodology of dealing with the machine and human operator separately made sense in the industrial age where all system intelligence was provided by the human, and the exclusively hardware-based machine was solely the product of hard science-based engineering. That is certainly no longer the case for even today's modern systems, and the distinction will continue to blur as more and more of the intelligence resides in and is endemic to the machine.
The nature of the interaction with human supervisory operators will begin to evolve based on our understanding of human–machine intelligence integration. A system that optimizes this interaction in a manner so that the integrated system performance well exceeds that of the independent sum of its parts
will likely prove to be a significant challenge for some time to come.
5 Summary
Despite a century plus of slow evolution, the unmanned air systems revolution is technologically still in its infancy. Continuing advances in computing power will enable ever more capable systems – exploiting enhanced logic and sensing to achieve more versatile platforms that enable new and diverse missions with an economic leverage as good as any to emanate from the revolution in robotic systems. The integrated regulatory, legal, social, and cultural landscape poses the greatest array of impediments to this advance, but an ever-increasing and compelling array of capabilities and applications appears to have the edge in shaping the future of this upstart niche in aviation and aerospace.
References
Chana, W. and Coleman, J. (1996) World's First VTOL Airplane Convair/Navy XFY-1 Pogo, SAE Technical Paper 962288. doi: 10.4271/962288.
Elston, J.S., Roadman, J., Stachura, M., Argrow, B., Houston, A., and Frew, E. (2011) The tempest unmanned aircraft system for in situ observations of tornadic supercells: design and VORTEX2 flight results. J. Field Robot., 28(4), 461–483.
Hager, G.D., Rus, D., Kumar, V., and Christensen, H. (2015) Toward a Science of Autonomy for Physical Systems, Computing Community Consortium, Ver. 1.
Holder, B. (2001) Unmanned Air Vehicles – An Illustrated Study of UAVs, Schiffer Publishing Ltd, Atglen, Pennsylvania.
Jenkins, D. and Vasigh, B. (2013) The Economic Impact of Unmanned Aircraft Systems Integration in the United States, Association of Unmanned Vehicle Systems International (AUVSI), Alexandria, Virginia.
Keane, J.F. and Carr, S.S. (2013) A Brief History of Early Unmanned Aircraft. Johns Hopkins Applied Physics Laboratory Technical Digest, 32(3), 558–571.
McMichael, J. and Francis, M. (1997) The micro air vehicle – toward a new dimension in flight, Unmanned Systems, vol. 15, Association of Unmanned Vehicle Systems International (AUVSI), Alexandria, Virginia, 10–17.
Newcome, L.R. (2004) Unmanned Aviation – A Brief History of Unmanned Air Vehicles, American Institute of Aeronautics and Astronautics (AIAA), Reston, Virginia.
Ruff, H.A., Narayanan, S., and Draper, M.H. (2002) Human interaction with levels of automation and decision-aid fidelity in the supervisory control of multiple simulated unmanned air vehicles. Presence – Teleoperators and Virtual Environments, vol. 11, MIT Press, Cambridge, UK, 335–351.
Tam, A. (2011) Public perception of unmanned aerial vehicles, Aviation Technology Graduate Student Publications. Paper 3, Purdue University e-Publications, 2011, Available at http://docs.lib.purdue.edu/atgrads/3.
Taylor, J.W. and Michael, J.H. (1977) Jane's Pocket Book of Research and Experimental Aircraft, Collier Books, New York.
Watts, A.C., Ambrosia, V.G., and Hinkley, E.A. (2012) Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sensing, 4(6), 1671–1692.
Part 2
Missions
Chapter 2
Remote Sensing Methodology for Unmanned Aerial Systems
Brandon J. Stark and Yang Quan Chen
School of Engineering, University of California, Merced, CA, USA
1 Introduction
2 UAS Remote Sensing Methodology
3 Core Concepts in UAS Remote Sensing Applications
4 UAS Imaging Equipment
5 Conclusion
References
1 Introduction
Unmanned aerial systems (UASs) have rapidly developed into a promising tool for remote sensing applications across a wide range of disciplines, from archeology to wildlife conservation. They can be designed and customized to fulfill a spectrum of characteristics and capabilities, such as low-altitude flying, long endurance, high maneuverability, and automated flight controls. But the UAS is simply the platform from which the target data are acquired. Unfortunately, with the multitude of UASs and combinations of sensing equipment, it can be a daunting challenge to determine the correct or cost-effective solution. The development of a thorough project methodology is an effective tool for addressing this challenge.
Section 2 of this chapter provides a guide to developing an effective methodology for UAS-based applications. Section 3 identifies several core attributes across three major types of remote sensing applications to guide the development of a methodology and influence equipment choices. Finally, in Section 4, imaging equipment attributes are discussed to provide guidance in their selection. While there are a multitude of different types of UASs and sensors, the chapter will utilize small UASs (<55 lb) and optical-based remote sensing as an example, although the overarching message is applicable for any UAS and sensing technique.
2 UAS Remote Sensing Methodology
It is far too easy for an application or project to be proposed with a UAS without a clear concept of the necessary methodology to address the problem. While public interest has fostered technological innovation, literature has been sparse of general methodology approaches for the unique challenges of UASs. Instead, UAS research is saturated with specific application with specialized workflows and methodologies unique for the immediate application. It has become necessary to promote methodology for the development of new applications and mature UASs.
An important challenge for the UAS project developers is to translate layman statements such as Let's use a drone to improve land management practices
into "Let's use a remote sensing platform carrying radiometrically calibrated optical imagers in the visible and near-infrared (NIR) spectra for the bare ground classification of a 10 square mile area with a desired optical resolution to discern the endemic population of Meadowfoam (Limnanthes alba)." The first statement is a wishful goal; the second introduces the methodology necessary to ensure a successful application and that the initial development and equipment purchases will lead to an effective solution.
An effective methodology defines the end goal, the activity, the implementation of the activity, the measurement of progress, and the success of the project. It provides a guideline for solving the targeted problem with specific tasks, components, and metrics. An incomplete or poorly defined project methodology can lead to development delays, spiraling costs, purchases of incorrect equipment, or complete project failure. In practice, many project developers find it useful to formulate a project methodology in terms of a series of questions such as the following (as adapted from Bhatta (2013)):
What is the purpose of the project?
What is the stated goal of the project?
Is the goal quantitative or qualitative?
Does this project utilize the scientific method or the technological method?
What objects or events are the desired outcomes related to?
Are there specific relationships found within the object or event of interest that can be utilized or must be taken into consideration?
What data are necessary to address the problem?
How should the data be collected?
What procedures should be used to analyze the data?
Are there available models/procedures sufficient to analyze the data?
Does it require developing new models/procedures?
What efforts must be undertaken to ensure the validity and reliability of the project?
What ethical issues need to be addressed?
Addressing the questions above and/or other clarifying questions about the proposed project is designed to help form connections between goal and implementation and identify specific methods that will enable the successful completion of the application or the project.
The first step in any project is to understand the goal with the intended purpose of narrowing down the language to actionable items. Simple classifications such as separating the goal between quantitative goals and qualitative goals are often useful in this regard. This step often requires a thorough understanding of the desired goal that may not always align with the wording of the stated goal. For example, a project with a purpose of improving crop yield
utilizes language that implies a qualitative goal, but in practice would require quantitative goals such as improve yield by 5%,
which implies accurate measurements to be achievable.
The method or body of techniques of the project is another example of a way to provide guidance to the development of an effective methodology.