Unmanned aerial vehicle
An unmanned aerial vehicle (UAV), commonly known as a drone, is an aircraft without a human pilot aboard. UAVs are a component of an unmanned aircraft system (UAS); which include a UAV, a ground-based controller, and a system of communications between the two. The flight of UAVs may operate with various degrees of autonomy: either under remote control by a human operator or autonomously by onboard computers.
Compared to manned aircraft, UAVs were originally used for missions too "dull, dirty or dangerous" for humans. While they originated mostly in military applications, their use is rapidly expanding to commercial, scientific, recreational, agricultural, and other applications, such as policing, peacekeeping, and surveillance, product deliveries, aerial photography, agriculture, smuggling, and drone racing. Civilian UAVs now vastly outnumber military UAVs, with estimates of over a million sold by 2015, so they can be seen as an early commercial application of autonomous things, to be followed by the autonomous car and home robots.
Multiple terms are used for unmanned aerial vehicles, which generally refer to the same concept.
The term drone, more widely used by the public, was coined in reference to the early remotely-flown target aircraft used for practice firing of a battleship's guns, and the term was first used with the 1920s Fairey Queen and 1930's de Havilland Queen Bee target aircraft. These two were followed in service by the similarly-named Airspeed Queen Wasp and Miles Queen Martinet, before ultimate replacement by the GAF Jindivik.
The term unmanned aircraft system (UAS) was adopted by the United States Department of Defense (DoD) and the United States Federal Aviation Administration in 2005 according to their Unmanned Aircraft System Roadmap 2005–2030. The International Civil Aviation Organization (ICAO) and the British Civil Aviation Authority adopted this term, also used in the European Union's Single-European-Sky (SES) Air-Traffic-Management (ATM) Research (SESAR Joint Undertaking) roadmap for 2020. This term emphasizes the importance of elements other than the aircraft. It includes elements such as ground control stations, data links and other support equipment. A similar term is an unmanned-aircraft vehicle system (UAVS), remotely piloted aerial vehicle (RPAV), remotely piloted aircraft system (RPAS). Many similar terms are in use.
A UAV is defined as a "powered, aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or nonlethal payload". Therefore, missiles are not considered UAVs because the vehicle itself is a weapon that is not reused, though it is also unmanned and in some cases remotely guided.
The relation of UAVs to remote controlled model aircraft is unclear. UAVs may or may not include model aircraft. Some jurisdictions base their definition on size or weight, however, the US Federal Aviation Administration defines any unmanned flying craft as a UAV regardless of size. For recreational uses, a drone (as apposed to a UAV) is a model aircraft that has first person video, autonomous capabilities or both.
In 1849 Austria sent unmanned, bomb-filled balloons to attack Venice. UAV innovations started in the early 1900s and originally focused on providing practice targets for training military personnel.
The earliest attempt at a powered UAV was A. M. Low's "Aerial Target" in 1916. Nikola Tesla described a fleet of unmanned aerial combat vehicles in 1915. Advances followed during and after World War I, including the Hewitt-Sperry Automatic Airplane. The first scaled remote piloted vehicle was developed by film star and model-airplane enthusiast Reginald Denny in 1935. More emerged during World War II – used both to train antiaircraft gunners and to fly attack missions. Nazi Germany produced and used various UAV aircraft during the war. Jet engines entered service after World War II in vehicles such as the Australian GAF Jindivik, and Teledyne Ryan Firebee I of 1951, while companies like Beechcraft offered their Model 1001 for the U.S. Navy in 1955. Nevertheless, they were little more than remote-controlled airplanes until the Vietnam War.
In 1959, the U.S. Air Force, concerned about losing pilots over hostile territory, began planning for the use of unmanned aircraft. Planning intensified after the Soviet Union shot down a U-2 in 1960. Within days, a highly classified UAV program started under the code name of "Red Wagon". The August 1964 clash in the Tonkin Gulf between naval units of the U.S. and North Vietnamese Navy initiated America's highly classified UAVs (Ryan Model 147, Ryan AQM-91 Firefly, Lockheed D-21) into their first combat missions of the Vietnam War. When the Chinese government showed photographs of downed U.S. UAVs via Wide World Photos, the official U.S. response was "no comment".
In 1973 the U.S. military officially confirmed that they had been using UAVs in Southeast Asia (Vietnam). Over 5,000 U.S. airmen had been killed and over 1,000 more were missing or captured. The USAF 100th Strategic Reconnaissance Wing flew about 3,435 UAV missions during the war at a cost of about 554 UAVs lost to all causes. In the words of USAF General George S. Brown, Commander, Air Force Systems Command, in 1972, "The only reason we need (UAVs) is that we don't want to needlessly expend the man in the cockpit." Later that year, General John C. Meyer, Commander in Chief, Strategic Air Command, stated, "we let the drone do the high-risk flying ... the loss rate is high, but we are willing to risk more of them ... they save lives!"
During the 1973 Yom Kippur War, Soviet-supplied surface-to-air missile batteries in Egypt and Syria caused heavy damage to Israeli fighter jets. As a result, Israel developed the first UAV with real-time surveillance. The images and radar decoys provided by these UAVs helped Israel to completely neutralize the Syrian air defenses at the start of the 1982 Lebanon War, resulting in no pilots downed. The first time UAVs were used as proof-of-concept of super-agility post-stall controlled flight in combat-flight simulations involved tailless, stealth technology-based, three-dimensional thrust vectoring flight control, jet-steering UAVs in Israel in 1987.
With the maturing and miniaturization of applicable technologies in the 1980s and 1990s, interest in UAVs grew within the higher echelons of the U.S. military. In the 1990s, the U.S. DoD gave a contract to AAI Corporation along with Israeli company Malat. The U.S. Navy bought the AAI Pioneer UAV that AAI and Malat developed jointly. Many of these UAVs saw service in the 1991 Gulf War. UAVs demonstrated the possibility of cheaper, more capable fighting machines, deployable without risk to aircrews. Initial generations primarily involved surveillance aircraft, but some carried armaments, such as the General Atomics MQ-1 Predator, that launched AGM-114 Hellfire air-to-ground missiles.
In 2013 at least 50 countries used UAVs. China, Iran, Israel and others designed and built their own varieties.
UAVs typically fall into one of six functional categories (although multi-role airframe platforms are becoming more prevalent):
- Target and decoy – providing ground and aerial gunnery a target that simulates an enemy aircraft or missile
- Reconnaissance – providing battlefield intelligence
- Combat – providing attack capability for high-risk missions (see unmanned combat aerial vehicle)
- Logistics – delivering cargo
- Research and development – improve UAV technologies
- Civil and commercial UAVs – agriculture, aerial photography, data collection
The U.S. Military UAV tier system is used by military planners to designate the various individual aircraft elements in an overall usage plan.
- Hand-held 2,000 ft (600 m) altitude, about 2 km range
- Close 5,000 ft (1,500 m) altitude, up to 10 km range
- NATO type 10,000 ft (3,000 m) altitude, up to 50 km range
- Tactical 18,000 ft (5,500 m) altitude, about 160 km range
- MALE (medium altitude, long endurance) up to 30,000 ft (9,000 m) and range over 200 km
- High-Altitude Long Endurance (high altitude, long endurance – HALE) over 30,000 ft (9,100 m) and indefinite range
- Hypersonic high-speed, supersonic (Mach 1–5) or hypersonic (Mach 5+) 50,000 ft (15,200 m) or suborbital altitude, range over 200 km
- Orbital low earth orbit (Mach 25+)
- CIS Lunar Earth-Moon transfer
- Computer Assisted Carrier Guidance System (CACGS) for UAVs
- Hobbyist UAVs – which can be further divided into
- Ready-to-fly (RTF)/Commercial-off-the-shelf (COTS)
- Bind-and-fly (BNF) – that require minimum knowledge to fly the platform
- Almost-ready-to-fly (ARF)/Do-it-yourself (DIY) – that require significant knowledge to get in the air.
- Midsize military and commercial UAVs
- Large military-specific UAVs
- Stealth combat UAVs
Classifications according to aircraft weight are quite simpler:
- Micro air vehicle (MAV) – the smallest UAVs that can weight less than 1g.
- Miniature UAV (also called SUAS) – approximately less than 25 kg.
- Heavier UAVs.
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Manned and unmanned aircraft of the same type generally have recognizably similar physical components. The main exceptions are the cockpit and environmental control system or life support systems. Some UAVs carry payloads (such as a camera) that weigh considerably less than an adult human, and as a result can be considerably smaller. Though they carry heavy payloads, weaponized military UAVs are lighter than their manned counterparts with comparable armaments.
Small civilian UAVs have no life-critical systems, and can thus be built out of lighter but less sturdy materials and shapes, and can use less robustly tested electronic control systems. For small UAVs, the quadcopter design has become popular, though this layout is rarely used for manned aircraft. Miniaturization means that less-powerful propulsion technologies can be used that are not feasible for manned aircraft, such as small electric motors and batteries.
Control systems for UAVs are often different than manned craft. For remote human control, a camera and video link almost always replace the cockpit windows; radio-transmitted digital commands replace physical cockpit controls. Autopilot software is used on both manned and unmanned aircraft, with varying feature sets.
The primary difference for planes is the absence of the cockpit area and its windows. Tailless quadcopters are a common form factor for rotary wing UAVs while tailed mono- and bi-copters are common for manned platforms.
Power supply and platformEdit
Small UAVs mostly use lithium-polymer batteries (Li-Po), while larger vehicles rely on conventional airplane engines.
UAV computing capability followed the advances of computing technology, beginning with analog controls and evolving into microcontrollers, then system-on-a-chip (SOC) and single-board computers (SBC).
System hardware for small UAVs is often called the Flight Controller (FC), Flight Controller Board (FCB) or Autopilot.
Position and movement sensors give information about the aircraft state. Exteroceptive sensors deal with external information like distance measurements, while exproprioceptive ones correlate internal and external states.
Non-cooperative sensors are able to detect targets autonomously so they are used for separation assurance and collision avoidance.
Degrees of freedom (DOF) refer to both the amount and quality of sensors on-board: 6 DOF implies 3-axis gyroscopes and accelerometers (a typical inertial measurement unit – IMU), 9 DOF refers to an IMU plus a compass, 10 DOF adds a barometer and 11 DOF usually adds a GPS receiver.
UAV actuators include digital electronic speed controllers (which control the RPM of the motors) linked to motors/engines and propellers, servomotors (for planes and helicopters mostly), weapons, payload actuators, LEDs and speakers.
UAV software called the flight stack or autopilot. UAVs are real-time systems that require rapid response to changing sensor data. Examples include Raspberry Pis, Beagleboards, etc. shielded with NavIO, PXFMini, etc. or designed from scratch such as Nuttx, preemptive-RT Linux, Xenomai, Orocos-Robot Operating System or DDS-ROS 2.0.
|Firmware||Time-critical||From machine code to processor execution, memory access…||ArduCopter-v1.px4|
|Middleware||Time-critical||Flight control, navigation, radio management...||Cleanflight, ArduPilot|
|Operating system||Computer-intensive||Optic flow, obstacle avoidance, SLAM, decision-making...||ROS, Nuttx, Linux distributions, Microsoft IOT|
List of civil-use open-source stacks include:
- DroneCode (forked from ArduCopter)
- BaseFlight (forked from MultiWii)
- CleanFlight (forked from BaseFlight)
- BetaFlight (forked from CleanFlight)
- RaceFlight (forked from CleanFlight)
- iNav (forked from CleanFlight)
- TauLabs (forked from OpenPilot)
- dRonin (forked from OpenPilot)
- LibrePilot (forked from OpenPilot)
UAVs employ open-loop, closed-loop or hybrid control architectures.
- Open loop—This type provides a positive control signal (faster, slower, left, right, up, down) without incorporating feedback from sensor data.
- Closed loop – This type incorporates sensor feedback to adjust behavior (reduce speed to reflect tailwind, move to altitude 300 feet). The PID controller is common. Sometimes, feedforward is employed, transferring the need to close the loop further.
Flight control is one of the lower-layer system and is similar to manned aviation: plane flight dynamics, control and automation, helicopter flight dynamics and controls and multirotor flight dynamics were researched long before the rise of UAVs.
Automatic flight involves multiple levels of priority.
UAVs can be programmed to perform aggressive manœuvres or landing/perching on inclined surfaces, and then to climb toward better communication spots. Some UAVs can control flight with varying flight modelisation, such as VTOL designs.
UAVs can also implement perching on a flat vertical surface.
Most UAVs use a radio frequency front-end that connects the antenna to the analog-to-digital converter and a flight computer that controls avionics (and that may be capable of autonomous or semi-autonomous operation).
In military systems and high-end domestic applications, downlink may convey payload management status. In civilian applications, most transmissions are commands from operator to vehicle. Downstream is mainly video. Telemetry is another kind of downstream link, transmitting status about the aircraft systems to the remote operator. UAVs use also satellite "uplink" to access satellite navigation systems.
The radio signal from the operator side can be issued from either:
- Ground control – a human operating a radio transmitter/receiver, a smartphone, a tablet, a computer, or the original meaning of a military ground control station (GCS). Recently control from wearable devices, human movement recognition, human brain waves was also demonstrated.
- Remote network system, such as satellite duplex data links for some military powers. Downstream digital video over mobile networks has also entered consumer markets, while direct UAV control uplink over the celullar mesh is under researched.
- Another aircraft, serving as a relay or mobile control station – military manned-unmanned teaming (MUM-T).
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ICAO classifies unmanned aircraft as either remotely piloted aircraft or fully autonomous. Actual UAVs may offer intermediate degrees of autonomy. E.g., a vehicle that is remotely piloted in most contexts may have an autonomous return-to-base operation.
Basic autonomy comes from proprioceptive sensors. Advanced autonomy calls for situational awareness, knowledge about the environment surrounding the aircraft from exterioceptive sensors: sensor fusion integrates information from multiple sensors.
One way to achieve autonomous control employs multiple control-loop layers, as in hierarchical control systems. As of 2016 the low-layer loops (i.e. for flight control) tick as fast as 32,000 times per second, while higher-level loops may cycle once per second. The principle is to decompose the aircraft's behavior into manageable "chunks", or states, with known transitions. Hierarchical control system types range from simple scripts to finite state machines, behavior trees and hierarchical task planners. The most common control mechanism used in these layers is the PID controller which can be used to achieve hover for a quadcopter by using data from the IMU to calculate precise inputs for the electronic speed controllers and motors.
Examples of mid-layer algorithms:
- Path planning: determining an optimal path for vehicle to follow while meeting mission objectives and constraints, such as obstacles or fuel requirements
- Trajectory generation (motion planning): determining control maneuvers to take in order to follow a given path or to go from one location to another
- Trajectory regulation: constraining a vehicle within some tolerance to a trajectory
UAV manufacturers often build in specific autonomous operations, such as:
- Self-level: attitude stabilization on the pitch and roll axes.
- Altitude hold: The aircraft maintains its altitude using barometric or ground sensors.
- Hover/position hold: Keep level pitch and roll, stable yaw heading and altitude while maintaining position using GNSS or inertal sensors.
- Headless mode: Pitch control relative to the position of the pilot rather than relative to the vehicle's axes.
- Care-free: automatic roll and yaw control while moving horizontally
- Take-off and landing (using a variety of aircraft or ground-based sensors and systems; see also:Autoland)
- Failsafe: automatic landing or return-to-home upon loss of control signal
- Return-to-home: Fly back to the point of takeoff (often gaining altitude first to avoid possible intervening obstructions such as trees or buildings).
- Follow-me: Maintain relative position to a moving pilot or other object using GNSS, image recognition or homing beacon.
- GPS waypoint navigation: Using GNSS to navigate to an intermediate location on a travel path.
- Orbit around an object: Similar to Follow-me but continuously circle a target.
- Pre-programmed aerobatics (such as rolls and loops)
Full autonomy is available for specific tasks, such as airborne refueling or ground-based battery switching; but higher-level tasks call for greater computing, sensing and actuating capabilities. One approach to quantifying autonomous capabilities is based on OODA terminology, as suggested by a 2002 US Air Force Research Laboratory, and used in the table below:
|Perception/Situational awareness||Analysis/Coordination||Decision making||Capability|
|10||Fully Autonomous||Cognizant of all within battlespace||Coordinates as necessary||Capable of total independence||Requires little guidance to do job|
|9||Battlespace Swarm Cognizance||Battlespace inference – Intent of self and others (allied and foes).
Complex/Intense environment – on-board tracking
|Strategic group goals assigned
Enemy strategy inferred
|Distributed tactical group planning
Individual determination of tactical goal
Individual task planning/execution
Choose tactical targets
|Group accomplishment of strategic goal with no supervisory assistance|
|8||Battlespace Cognizance||Proximity inference – Intent of self and others (allied and foes)
Reduces dependence upon off-board data
|Strategic group goals assigned
Enemy tactics inferred
|Coordinated tactical group planning
Individual task planning/execution
Choose target of opportunity
|Group accomplishment of strategic goal with minimal supervisory assistance
(example: go SCUD hunting)
|7||Battlespace Knowledge||Short track awareness – History and predictive battlespace
Data in limited range, timeframe and numbers
Limited inference supplemented by off-board data
|Tactical group goals assigned
Enemy trajectory estimated
|Individual task planning/execution to meet goals||Group accomplishment of tactical goals with minimal supervisory assistance|
|Ranged awareness – on-board sensing for long range,
supplemented by off-board data
|Tactical group goals assigned
Enemy trajectory sensed/estimated
|Coordinated trajectory planning and execution to meet goals – group optimization||Group accomplishment of tactical goals with minimal supervisory assistance
Possible: close air space separation (+/-100yds) for AAR, formation in non-threat conditions
|Sensed awareness – Local sensors to detect others,
Fused with off-board data
|Tactical group plan assigned
RT Health Diagnosis Ability to compensate
for most failures and flight conditions;
Ability to predict onset of failures
(e.g. Prognostic Health Mgmt)
Group diagnosis and resource management
|On-board trajectory replanning – optimizes for current and predictive conditions
|Self accomplishment of tactical plan as externally assigned
Medium vehicle airspace separation (hundreds of yds)
|Deliberate awareness – allies communicate data||Tactical group plan assigned
Assigned Rules of Engagement
RT Health Diagnosis; Ability to compensate
for most failures and flight conditions – inner loop changes reflected in outer loop performance
|On-board trajectory replanning – event driven
Self resource management
|Self accomplishment of tactical plan as externally assigned
Medium vehicle airspace separation (hundreds of yds)
|3||Robust Response to Real Time Faults/Events||Health/status history & models||Tactical group plan assigned
RT Health Diagnosis (What is the extent of the problems?)
Ability to compensate for most failures and flight conditions (i.e. adaptative inner loop control)
|Evaluate status vs required mission capabilities
Abort/RTB is insufficient
|Self accomplishment of tactical plan as externally assigned|
|2||Changeable mission||Health/status sensors||RT Health diagnosis (Do I have problems?)
Off-board replan (as required)
|Execute preprogrammed or uploaded plans
in response to mission and health conditions
|Self accomplishment of tactical plan as externally assigned|
|Preloaded mission data
Flight Control and Navigation Sensing
|Pre/Post flight BIT
|Preprogrammed mission and abort plans||Wide airspace separation requirements (miles)|
|Flight Control (attitude, rates) sensing
Remote pilot commands
|N/A||Control by remote pilot|
Medium levels of autonomy, such as reactive autonomy and high levels using cognitive autonomy, have already been achieved to some extent and are very active research fields.
Reactive autonomy, such as collective flight, real-time collision avoidance, wall following and corridor centring, relies on telecommunication and situational awareness provided by range sensors: optic flow, lidars (light radars), radars, sonars.
Most range sensors analyze electromagnetic radiation, reflected off the environment and coming to the sensor. The cameras (for visual flow) act as simple receivers. Lidars, radars and sonars (with sound mechanical waves) emit and receive waves, measuring the round-trip transit time. UAV cameras do not require emitting power, reducing total consumption.
Radars and sonars are mostly used for military applications.
Reactive autonomy has in some forms already reached consumer markets: it may be widely available in less than a decade.
Simultaneous localization and mappingEdit
SLAM combines odometry and external data to represent the world and the position of the UAV in it in three dimensions. High-altitude outdoor navigation does not require large vertical fields-of-view and can rely on GPS coordinates (which makes it simple mapping rather than SLAM).
Two related research fields are photogrammetry and LIDAR, especially in low-altitude and indoor 3D environments.
- Indoor photogrammetric and stereophotogrammetric SLAM has been demonstrated with quadcopters.
- Lidar platforms with heavy, costly and gimbaled traditional laser platforms are proven. Research attempts to address production cost, 2D to 3D expansion, power-to-range ratio, weight and dimensions. LED range-finding applications are commercialized for low-distance sensing capabilities. Research investigates hybridization between light emission and computing power: phased array spatial light modulators, and frequency-modulated-continuous-wave (FMCW) MEMS-tunable vertical-cavity surface-emitting lasers (VCSELs).
Robot swarming refers to networks of agents able to dynamically reconfigure as elements leave or enter the network. They provide greater flexibility than multi-agent cooperation. Swarming may open the path to data fusion. Some bio-inspired flight swarms use steering behaviors and flocking.[clarification needed]
Future military potentialEdit
In the military sector, American Predators and Reapers are made for counterterrorism operations and in war zones in which the enemy lacks sufficient firepower to shoot them down. They are not designed to withstand antiaircraft defenses or air-to-air combat. In September 2013, the chief of the US Air Combat Command stated that current UAVs were "useless in a contested environment" unless manned aircraft were there to protect them. A 2012 Congressional Research Service (CRS) report speculated that in the future, UAVs may be able to perform tasks beyond intelligence, surveillance, reconnaissance and strikes; the CRS report listed air-to-air combat ("a more difficult future task") as possible future undertakings. The Department of Defense's Unmanned Systems Integrated Roadmap FY2013-2038 foresees a more important place for UAVs in combat. Issues include extended capabilities, human-UAV interaction, managing increased information flux, increased autonomy and developing UAV-specific munitions. DARPA's project of systems of systems, or General Atomics work may augur future warfare scenarios, the latter disclosing Avenger swarms equipped with High Energy Liquid Laser Area Defense System (HELLADS).
The global military UAV market is dominated by United States and Israel companies. By sale numbers, The US held over 60% military-market share in 2017. Four of top five military UAV manufactures are American including General Atomics, Lockheed Martin, Northrop Grumman and Boeing, followed by the Chinese company CASC. Israel companies mainly focus on small surveillance UAV system and by quantity of drones, Israel exported 60.7% (2014) of UAV on the market while the United States export 23.9% (2014); top importers of military UAV are The United Kingdom (33.9%) and India (13.2%). United States alone operated over 9,000 military UAVs in 2014. General Atomics is the dominant manufacturer with the Global Hawk and Predator/Mariner systems product-line.
The consumer drone market is dominated by Chinese companies. Chinese drone manufacturer DJI alone has 75% of civilian-market share in 2017 with $11 billion forecast global sales in 2020. Followed by French company Parrot with $110m and US company 3DRobotics with $21.6m in 2014. As of March 2017, more than 770,000 civilian UAVs were registered with the U.S. FAA, though it is estimated more than 1.1 million have been sold in the United States alone.
Civilian UAV market is relatively new compare to military. Companies are emerging in both developed and developing nations at the same time. Many early stage startups have received support and funding from investors like in United States and by government agencies as the case in India. Some universities offer research and training programs or degrees. Private entities also provide online and in-person training programs for both recreational and commercial UAV use.
The AIA reports large cargo and passengers drones should be certified and introduced over the next 20 years. Sensor-carrying large drones are expected from 2018; short-haul, low altitude freighters outside cities from 2025; long-haul cargo flights by the mid-2030s and then passenger flights by 2040. Spending should rise from a few hundred million dollars on research and development in 2018 to $4 billion by 2028 and $30 billion by 2036.
Animal imitation – EthologyEdit
The Nano Hummingbird is commercially available, while sub-1g microUAVs inspired by flies, albeit using a power tether, can "land" on vertical surfaces.
Other projects include unmanned "beetles" and other insects.
Research is exploring miniature optic-flow sensors, called ocellis, mimicking the compound insect eyes formed from multiple facets, which can transmit data to neuromorphic chips able to treat optic flow as well as light intensity discrepancies.
UAV endurance is not constrained by the physiological capabilities of a human pilot.
Because of their small size, low weight, low vibration and high power to weight ratio, Wankel rotary engines are used in many large UAVs. Their engine rotors cannot seize; the engine is not susceptible to shock-cooling during descent and it does not require an enriched fuel mixture for cooling at high power. These attributes reduce fuel usage, increasing range or payload.
Solar-electric UAVs, a concept originally championed by the AstroFlight Sunrise in 1974, have achieved flight times of several weeks.
Solar-powered atmospheric satellites ("atmosats") designed for operating at altitudes exceeding 20 km (12 miles, or 60,000 feet) for as long as five years could potentially perform duties more economically and with more versatility than low earth orbit satellites. Likely applications include weather monitoring, disaster recovery, earth imaging and communications.
Electric UAVs powered by microwave power transmission or laser power beaming are other potential endurance solutions.
Another application for a high endurance UAV would be to "stare" at a battlefield for a long interval (ARGUS-IS, Gorgon Stare, Integrated Sensor Is Structure) to record events that could then be played backwards to track battlefield activities.
|Boeing Condor||58:11||1989||The aircraft is currently in the Hiller Aviation Museum.|
|General Atomics GNAT||40:00||1992|||
|TAM-5||38:52||11 August 2003||Smallest UAV to cross the Atlantic|
|QinetiQ Zephyr Solar Electric||54:00||September 2007|||
|RQ-4 Global Hawk||33:06||22 March 2008||Set an endurance record for a full-scale, operational unmanned aircraft.|
|QinetiQ Zephyr Solar Electric||82:37||28–31 July 2008|||
|QinetiQ Zephyr Solar Electric||336:22||9–23 July 2010|||
Individual reliability covers robustness of flight controllers, to ensure safety without excessive redundancy to minimize cost and weight. Besides, dynamic assessment of flight envelope allows damage-resilient UAVs, using non-linear analysis with ad-hoc designed loops or neural networks. UAV software liability is bending toward the design and certifications of manned avionics software.
Swarm resilience involves maintaining operational capabilities and reconfiguring tasks given unita failures.
There are numerous civilian, commercial, military, and aerospace applications for UAVs. These include:
- Disaster relief, archeology, conservation (pollution monitoring and anti-poaching), law enforcement, crime, and terrorism
- Aerial surveillance, filmmaking, journalism, scientific research, surveying, cargo transport, and agriculture
- Reconnaissance, attack, demining, and target practice
The export of UAVs or technology capable of carrying a 500 kg payload at least 300 km is restricted in many countries by the Missile Technology Control Regime.
Safety and securityEdit
UAVs can threaten airspace security in numerous ways, including unintentional collisions or other interference with other aircraft, deliberate attacks or by distracting pilots or flight controllers. The first incident of a drone-airplane collision occurred in mid-October 2017 in Quebec City, Canada.
UAVs could be loaded with dangerous payloads, and crashed into vulnerable targets. Payloads could include explosives, chemical, radiologial or biological hazards. UAVs with generally non-lethal payloads could possibly be hacked and put to malicious purposes. Anti-UAV systems are being developed by states to counter this threat. This is, however, proving difficult. As Dr J. Rogers stated in an interview to A&T "There is a big debate out there at the moment about what the best way is to counter these small UAVs, whether they are used by hobbyists causing a bit of a nuisance or in a more sinister manner by a terrorist actor.”
By 2017, drones were being used to drop contraband into prisons.
The interest in UAVs cyber security has been raised greatly after the Predator UAV video stream hijacking incident in 2009, where Islamic militants used cheap, off-the-shelf equipment to stream video feeds from a UAV. Another risk is the possibility of hijacking or jamming a UAV in flight. In recent years several security researchers have made public vulnerabilities for commercial UAVs, in some cases even providing full source code or tools to reproduce their attacks. At a workshop on UAVs and privacy in October 2016, researchers from the Federal Trade Commission showed they were able to hack into three different consumer quadcopters and noted that UAV manufacturers can make their UAVs more secure by the basic security measures of encrypting the Wi-Fi signal and adding password protection.
In the United States, flying close to a wildfire is punishable by a maximum $25,000 fine. Nonetheless, in 2014 and 2015, firefighting air support in California was hindered on several occasions, including at the Lake Fire and the North Fire. In response, California legislators introduced a bill that would allow firefighters to disable UAVs which invaded restricted airspace. The FAA later required registration of most UAVs.
Ethical concerns and UAV-related accidents have driven nations to regulate the use of UAVs.
In 2016 Transport Canada proposed the implementation of new regulations that would require all UAVs over 250 grams to be registered and insured and that operators would be required to be a minimum age and pass an exam in order to get a license. These regulations are expected to be introduced in 2018. (http://www.gazette.gc.ca/rp-pr/p1/2017/2017-07-15/html/reg2-eng.php)
In April 2014, the South African Civil Aviation Authority announced that it would clamp down on the illegal flying of UAVs in South African airspace. "Hobby drones" with a weight of less than 7 kg at altitudes up to 500m with restricted visual line-of-sight below the height of the highest obstacle within 300m of the UAV are allowed. No license is required for such vehicles.
The ENAC (Ente Nazionale per l'Aviazione Civile), that is, the Italian Civil Aviation Authority for technical regulation, certification, supervision and control in the field of civil aviation, issued on May 31, 2016 a very detailed regulation for all UAV, determining which types of vehicles can be used, where, for which purposes, and who can control them. The regulation deals with the usage of UAV for either commercial and recreational use. Last version was published on December 22, 2016.
From 21 December 2015 all hobby type UAV's between 250 grams and 25 kilograms needed to be registered with FAA no later than 19 February 2016.
The new FAA UAV registration process includes requirements for:
- Eligible owners must register their UAV's prior to flight.
- If the owner is less than 13 years old, a parent or other responsible person must do the FAA registration.
- UAV's must be marked with the FAA-issued registration number.
- The registration fee is $5. The registration is good for 3 years and can be renewed for an additional 3 years at the $5 rate.
- A single registration applies to all UAVs owned by an individual. Failure to register can result in civil penalties of up to $27,500 and criminal penalties of up to $250,000 and/or imprisonment for up to three years.
On May 19, 2017, in the case Taylor v. Huerta, the U.S. Court of Appeals for the District of Columbia Circuit held that that the FAA's 2015 drone registration rules were in violation of the 2012 FAA Modernization and Reform Act. Under the court's holding, although commercial drone operators are required to register, recreational operators are not. On May 25, 2017, one week after the Taylor decision, Senator Diane Feinstein introduced S. 1272, the Drone Federalism Act of 2017, in Congress.
On 21 June 2016 the Federal Aviation Administration announced regulations for commercial operation of small UAS craft (sUAS), those between 0.55 and 55 pounds (about 250 gm to 25 kg) including payload. The rules, which exclude hobbyists, require the presence at all operations of a licensed Remote Pilot in Command. Certification of this position, available to any citizen at least 16 years of age, is obtained solely by passing a written test and then submitting an application. For those holding a sport pilot license or higher, and with a current flight review, a rule-specific exam can be taken at no charge online at the faasafety.gov website. Other applicants must take a more comprehensive examination at an aeronautical testing center. All licensees are required to take a review course every two years. At this time no ratings for heavier UAS are available.
Commercial operation is restricted to daylight, line-of-sight, under 100 mph, under 400 feet, and Class G airspace only, and may not fly over people or be operated from a moving vehicle. Some organizations have obtained a waiver or Certificate of Authorization that allows them to exceed these rules. For example, CNN has obtained a waiver for UAVs modified for injury prevention to fly over people, and other waivers allow night flying with special lighting, or non-line-of-sight operations for agriculture or railroad track inspection.
Previous to this announcement, any commercial use required a full pilot's license and an FAA waiver, of which hundreds had been granted.
The use of UAVs for law-enforcement purposes is regulated at a state level.
As of December 20, 2017, UAV's of 250g or less are not controlled by the CAA guidances that include maintaining 50 meters from person, animal or property.
The UAV must still not go higher than 400 ft with a single pilot or 1000 ft with a pilot and spotter, however as with UAV's above 300g, if within 400 ft of a structure, you are allowed to go 400 ft higher than the structure.
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Research and groupsEdit
- Center for Unmanned Aircraft Systems, a National Science Foundation Industry & University Cooperative Research Center
- UVS International Non Profit Organization representing manufacturers of unmanned vehicle systems (UVS), subsystems and critical components for UVS and associated equipment, as well as companies supplying services with or for UVS, research organizations and academia.
- [permanent dead link] The Remote Control Aerial Platform Association, commercial UAS operators
- Cities and Drones National League of Cities report on urban government use and regulation of UAS equipment
- Drones and Drone Data Technical Interest Group (TIG) Technology and techniques (equipment, software, workflows, survey designs) to allow individuals to enhance their capabilities with data obtained from drones and drone surveys. Chaired by Karl Osvald and James McDonald.
- Garcia-Bernardo, Sheridan Dodds, F. Johnson (2016). "Quantitative patterns in drone wars" (PDF). Science direct.
- Hill, J., & Rogers, A. (2014). The rise of the drones: From The Great War to Gaza. Vancouver Island University Arts & Humanities Colloquium Series.
- Rogers, A., & Hill, J. (2014). Unmanned: Drone warfare and global security. Between the Lines. ISBN 9781771131544
- How Intelligent Drones Are Shaping the Future of Warfare, Rolling Stone Magazine