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.
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 (UCAV))
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.
Schiebel S-100 fitted with a Lightweight Multirole Missile
Vehicles can be categorised in terms of range/altitude. The following has been advanced as relevant at industry events such as ParcAberporth Unmanned Systems forum:
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
HALE (high altitude, long endurance) 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
Other categories include:
Hobbyist UAVs – which can be further divided into
Ready-to-fly (RTF)/Commercial-off-the-shelf (COTS)
Bind-and-fly (BNF) – require minimum knowledge to fly the platform
Almost-ready-to-fly (ARF)/Do-it-yourself (DIY) – require significant knowledge to get in the air
Bare frame – requires significant knowledge and your own parts to get it in the air
Midsize military and commercial UAVs
Large military-specific UAVs
Stealth combat UAVs
Unmanned Versatile Aircraft (originally a 2-seater Pipistrel Sinus)
Manned aircraft transformed into unmanned (and Optionally Piloted UAVs or OpVs)
Classifications according to aircraft weight are quite simpler:
Micro air vehicle (MAV) – the smallest UAVs that can weigh less than 1g
Miniature UAV (also called SUAS) – approximately less than 25 kg
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 platform
Small UAVs mostly use lithium-polymer batteries (Li-Po), while larger vehicles rely on conventional airplane engines. Scale or size of aircraft is not the defining or limiting characteristic of energy supply for a UAV. At present,[when?] the energy density of Li-Po is far less than gasoline. The record of travel for a UAV (built from balsa wood and mylar skin) across the North Atlantic Ocean is held by a gasoline model airplane or UAV. Manard Hill in “in 2003 when one of his creations flew 1,882 miles across the Atlantic Ocean on less than a gallon of fuel” holds this record. See: Electric power is used as less work is required for a flight and electric motors are quieter. Also, properly designed, the thrust to weight ratio for an electric or gasoline motor driving a propeller can hover or climb vertically. Botmite airplane is an example of an electric UAV which can climb vertically.
Battery elimination circuitry (BEC) is used to centralize power distribution and often harbors a microcontroller unit (MCU). Costlier switching BECs diminish heating on the platform.
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) refers 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.
Flight stack overview
|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|
Civil-use open-source stacks include:
DroneCode (forked from ArduCopter)
BaseFlight (forked from MultiWii)
CleanFlight (forked from BaseFlight)
BetaFlight (forked from CleanFlight)
iNav (forked from CleanFlight)
RaceFlight (forked from CleanFlight)
dRonin (forked from OpenPilot)
LibrePilot (forked from OpenPilot)
TauLabs (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.
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 for remote control and exchange of video and other data. Early UAVs had only Narrowband uplink. Downlinks came later. These bi-directional narrowband radio links carried Command and Control (C&C) and Telemetry data about the status of aircraft systems to the remote operator. For very long range flights, military UAVs also use satellite receivers as part of satellite navigation systems. In cases when video transmission was required, the UAVs will implement a separate analog video radio link.
In the most modern UAV applications, video transmission is required. So instead of having 2 separate links for C&C, Telemetry and Video traffic, a Broadband link is used to carry all types of data on the a single radio link. These broadband links can leverage Quality of service techniques to optimize the C&C traffic for low latency. Usually these broadband links carry TCP/IP traffic that can be routed over the Internet.
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 and LTE have been demonstrated and are in trials.
Another aircraft, serving as a relay or mobile control station – military manned-unmanned teaming (MUM-T).
A protocol MAVLink is increasingly becoming popular to carry Command and Control data between the Ground control and the vehicle
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
Evolved UAV hierarchical task planners use methods like state tree searches or genetic algorithms.
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:
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 mapping
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 potential
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).
Cognitive radio[clarification needed] technology may have UAV applications.
UAVs may exploit distributed neural networks.
The global military UAV market is dominated by companies based in the United States and Israel. 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 civilian 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 2018, more than one million UAVs (878,000 hobbyist and 122,000 commercial) were registered with the U.S. FAA. 2018 NPD point to consumers increasingly purchasing drones with more advanced features with 33 percent growth in both the $500+ and $1000+ market segments.
Civilian UAV market is relatively new compared 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.
Consumer drones are also widely used by military organizations worldwide because of the cost-effective nature of consumer product. In 2018, Israeli military started to use DJI Mavic and Matrice series of UAV for light reconnaissance mission since the civilian drones are easier to use and have higher reliability. DJI drones is also the most widely used commercial unmanned aerial system that the US Army has employed.
Lighted drones are beginning to be used in nighttime displays for artistic and advertising purposes.
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 – ethology
Flapping-wing ornithopters, imitating birds or insects, are a research field in microUAVs. Their inherent stealth recommends them for spy missions.
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.
Proper drone cooling is essential for long-term drone endurance. Overheating and subsequent engine failure is the most common cause of drone failure.
Hydrogen fuel cells, using hydrogen power, may be able to extend the endurance of small UAVs, up to several hours.
Micro air vehicles endurance is so far best achieved with flapping-wing UAVs, followed by planes and multirotors standing last, due to lower Reynolds number.
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.
Lengthy endurance flights
|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|
Reliability improvements target all aspects of UAV systems, using resilience engineering and fault tolerance techniques.
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 unit 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
UAVs are being developed and deployed by many countries around the world. Due to their wide proliferation, no comprehensive list of UAV systems exists.
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 security
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. The first recorded instance of a drone collision with a hot air balloon occurred on 10 August 2018 in Driggs, Idaho, United States; although there was no significant damage to the balloon nor any injuries to its 3 occupants, the balloon pilot reported the incident to the NTSB, stating that “I hope this incident helps create a conversation of respect for nature, the airspace, and rules and regulations.”
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. Several security researchers have made public some vulnerabilities in 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.
The use of UAVs is also being investigated to help detect and fight wildfires, whether through observation or launching pyrotechnic devices to start backfires.
Source from Wikipedia