AI News, Autonomous Robots in the Fog of War
Autonomous Robots in the Fog of War
Two small planes fly low over a village, methodically scanning the streets below.
The demonstration may sound simple—the target was just a tarp staked to the ground—but had this been the streets of Kabul or Baghdad, where any pile of debris can conceal a deadly improvised explosive device, such autonomous tracking robots in the future could help keep soldiers out of harm’s way.
Indeed, military leaders have increasingly embraced the use of unmanned aerial vehicles (UAVs) and other robotic systems over the past decade, to handle the “three D’s”: the dull, dirty, and dangerous tasks of war.
The ranks of battlefield robots will only grow: The U.S. Congress has mandated that by the year 2015, one-third of ground combat vehicles will be unmanned, and the DOD is now developing a multitude of unmanned systems that it intends to rapidly field.
If we are ever to see fully autonomous robots enter the battlefield—those capable of planning and carrying out missions and learning from their experiences—several key technological advances are needed, including improved sensing, more agile testing, and seamless interoperability.
He seems to assume it’s a given: Robots will someday be agile enough to create exact copies of their mechanical bodies and of the software code comprising their “brains.” All he wants to know from me is when—not if—this great day will arrive.
As a researcher at the Georgia Tech Research Institute and a board member of the world’s largest association for unmanned systems—the Association for Unmanned Vehicle Systems International—I’ve been working with robots for more than two decades, starting with underwater vehicles, then moving to air and ground vehicles, and most recently addressing collaborations among robots like those we demonstrated at the Robotics Rodeo.
Unmanned maritime vehicles include submarine-like vessels that can cruise underwater for kilometers and boatlike craft that patrol for pirates, smugglers, and other criminal types.
The RQ-4 Global Hawk UAV, made by Northrop Grumman, is guided by satellite waypoint navigation, yet it still requires a human pilot sitting in a remote ground station, plus others to operate the drone’s sensors and analyze the data being sent back.
Although the most advanced robots these days may gather data from an expansive array of cameras, microphones, and other sensors, they lack the ability to process all that information in real time and then intelligently act on the results.
To appreciate the enormous challenge of robotic sensing, consider this factoid, reported last year in The Economist: “During 2009, American drone aircraft…sent back 24 years’ worth of video footage.
New models...will provide ten times as many data streams…and those in 2011 will produce 30 times as many.” It’s statistics such as those that once prompted colleagues of mine to print up lanyards that read “It’s the Sensor, Stupid.” But a robot is more than just a platform of sensors.
An autonomous robot needs to be able to automatically process the data from those sensors, extract relevant information from those data, and then make decisions in real time based on that information and on information it has gathered in the past.
If a robo-sentry armed with a semiautomatic rifle detects someone running from a store, how can it know whether that person has just robbed the store or is simply sprinting to catch a bus?
If a fully autonomous, unmanned system were to make such a grave mistake, it could compromise the safety of other manned and unmanned systems and exacerbate the political situation.
Countless factors can affect the outcome of a given test: the robot’s cognitive information processing, external stimuli, variations in the operational environment, hardware and software failures, false stimuli, and any new and unexpected situation a robot might encounter.
By watching which areas of the brain experience greater blood flow and neuronal activity in certain situations, neuroscientists gain a better understanding of how the brain operates.
Another illuminating form of testing that is often skipped in the rush to deploy today’s military robots involves simply playing with the machines on an experimental “playground.” The playground has well-defined boundaries and safety constraints that allow humans as well as other robots to interact with the test robot and observe its behavior.
Each tread-wheeled bot, looking like a tiny tank with a mastlike antenna sticking out of its top, investigates the floor space around it using a video camera to identify windows and doors and a laser scanner to measure distances.
Rather than having a fixed architecture, it will have swappable “mission modules” that include vertical takeoff unmanned aerial vehicles, unmanned underwater vehicles, and unmanned surface vehicles.
All these robotic systems will have to operate in concert with each other as well as with manned systems, to support intelligence, surveillance, and reconnaissance missions, oceanographic surveys, mine warfare, port security, and so on.
While significant progress has been made on automating a single robot as well as a team of identical robots, we are not yet at the point where an unmanned system built for the Army by one contractor can seamlessly interact with another robotic system built for the Navy by another contractor.
Unmanned aerial vehicle
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.
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 War of Attrition (1967–1970) featured the introduction of UAVs with reconnaissance cameras into combat in the Middle East. In the 1973 Yom Kippur War Israel used UAVs as decoys to spur opposing forces into wasting expensive anti-aircraft missiles. 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.
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.
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): The U.S. Military UAV tier system is used by military planners to designate the various individual aircraft elements in an overall usage plan.
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.
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: Evolved UAV hierarchical task planners use methods like state tree searches or genetic algorithms. UAV manufacturers often build in specific autonomous operations, such as: Full autonomy is available for specific tasks, such as airborne refueling or ground-based battery switching;
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 United States and Israel 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.
Many early stage startups have received support and funding from investors like United States and government agencies such as 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. Flapping-wing ornithopters, imitating birds or insects, are a research field in microUAVs.
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.
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.
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.
Rogers stated in an interview to AT '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.
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.
The Irish Aviation Authority (IAA) requires all UAVs over 1 kg to be registered with UAVs weighing 4 kg or more requiring a license to be issued by the IAA. As of May 2016[update], the Dutch police are testing trained bald eagles to intercept offending 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.
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.
Unmanned ground vehicle
An unmanned ground vehicle (UGV) is a vehicle that operates while in contact with the ground and without an onboard human presence.
Based on its application, unmanned ground vehicles will generally include the following components: platform, sensors, control systems, guidance interface, communication links, and systems integration features. The platform can be based on an all-terrain vehicle design and includes the locomotive apparatus, sensors, and power source.
Sensors can include compasses, odometers, inclinometers, gyroscopes, cameras for triangulation, laser and ultrasound range finders, and infrared technology. Unmanned ground vehicles are generally considered Remote-Operated and Autonomous, although Supervisory Control is also used to refer to situations where there is a combination of decision making from internal UGV systems and the remote human operator. A
Some examples of autonomous UGV technology are: Depending on the type of control system, the interface between machine and human operator can include joystick, computer programs, or voice command. Communication between UGV and control station can be done via radio control or fiber optics.
Military applications include surveillance, reconnaissance, and target acquisition. They are also used in industries such as agriculture, mining and construction. UGVs are also being developed for peacekeeping operations, ground surveillance, gatekeeper/checkpoint operations, urban street presence and to enhance police and military raids in urban settings.
UGVs can 'draw first fire' from insurgents — reducing military and police casualties. Furthermore, UGVs are now being used in rescue and recovery mission and were first used to find survivors following 9/11 at Ground Zero. NASA's Mars Exploration Rover project includes two UGVs, Spirit and Opportunity, that are still performing beyond original design parameters.
This is attributed to redundant systems, careful handling, and long-term interface decision making. Opportunity (rover) and its twin, Spirit (rover), six-wheeled, solar powered ground vehicles, were launched in July 2003 and landed on opposite sides of Mars in January 2004.
The Spirit rover operated nominally until it became trapped in deep sand in April 2009, lasting more than 20 times longer than expected. Opportunity, by comparison, has been operational for more than 12 years beyond its intended lifespan of three months.
Aerospace companies use these vehicles for precision positioning and transporting heavy, bulky pieces between manufacturing stations, which is less time-consuming than using large cranes and can keep people from engaging with dangerous areas. UGVs can be used to traverse and map mine tunnels. Combining radar, laser, and visual sensors, UGVs are in development to map 3D rock surfaces in open pit mines. In the warehouse management system, UGVs have multiple uses from transferring goods with autonomous forklifts and conveyors to stock scanning and taking inventory. UGVs are used in many emergency situations including Urban search and rescue, fire fighting, and nuclear response. Following the 2011 Fukushima Daiichi Nuclear Power Plant accident, UGVs were used in Japan for mapping and structural assessment in areas with too much radiation to warrant a human presence. UGV use by the military has saved many lives.
Applications include explosive ordnance disposal (EOD) such as landmines, loading heavy items, and repairing ground conditions under enemy fire. The number of robots used in Iraq increased from 150 in 2004 to 5000 in 2005 and they disarmed over 1000 roadside bombs in Iraq at the end of 2005 (Carafano
By 2013, the U.S. Army had purchased 7,000 such machines and 750 had been destroyed. The military is using UGV technology to develop robots outfitted with machine guns and grenade launchers that may replace soldiers. SARGE is based on a 4-wheel drive all terrain vehicle;
Moreover, the SWORDS can use their weapons with extreme precision, hitting the bull’s-eye of a target 70/70 times. These robots are capable of withstanding a lot of damage, including multiple 0.50 inch bullets, or a fall from a helicopter onto concrete. In addition, the SWORDS robot is even capable of making its way through virtually any terrain, including underwater. In 2004, only four SWORDS units were in existence although 18 were requested for service overseas.
They are currently remotely operated but future plans are to include an autonomous artificial intelligence system. In 2015, Rostec unveiled the Uran-9 unmanned combat ground vehicle. According to a release by Rosoboronexport, the system will be designed to deliver combined combat, reconnaissance and counter-terrorism units with remote reconnaissance and fire support. Armament includes a 7.62 mm machine gun and four 9M120 Ataka anti-tank missiles.
Vehicles that carry, but are not operated by a human, are not technically unmanned ground vehicles, however, the technology for development is similar. The coModule electric bicycle is fully controllable via smartphone, with users able to accelerate, turn and brake the bike by tilting their device.
Formal verification of ethical choices in autonomous systems
Autonomous systems such as unmanned vehicles are beginning to operate within society.
Inevitably an autonomous system will find itself in a situation in which it needs to not only choose to obey a rule or not, but also make a complex ethical decision.
We implement a rational agent that incorporates a given ethical policy in its plan selection and show that we can formally verify that the agent chooses to execute, to the best of its beliefs, the most ethical available plan.
- On Thursday, September 19, 2019
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