Criminals and militants have now started using swarm of commercial available drones thereby engancing their effectiveness and lethality. Military is also developing swarms for many applications including ISR, decoys or as swarm of weapons. Swarms are expected to be effective even in A2/AD environments.
Instead of being individually directed by a human controller, the basic idea of a drone swarm is that its machines are able to make decisions among themselves. So far the technology has been at an experimental stage, but it is edging closer to becoming a reality.
However, many of applications like improved disaster response and unique vehicles for transportation are still stuck in the lab or still in concept phase. The main factors holding back swarming robotics are the stigma of widespread robots, the lack of reliable communications, readily available distributed algorithms, and the cost of individual robots. However, these are quickly changing and the concerns can be mitigated by designing safeguards into these complex systems, writes Jason Ernst, PhD Candidate, CS, is the CTO of Redtree Robotics. The sensors, cameras, motors and other parts that make the robot work are all expensive, however the scale of mobile phones have made some of the key sensors like accelerometer, gyroscope, GPS have become insanely cheap.
The robots need to exchange positions, direction of motion, pitch, yaw, roll, and they may need to also keep track of information about the task they are solving, there is a lack of coordinated algorithms readily available writes Jason.
In turn, holding back the development of coordinated algorithms is the lack of reliable, robust communications between robots. For swarm to become a reality, robots must communicate with each other directly, in addition to communicating to the Internet. This means local meshes must be setup between robots. The communications stack must be smart enough to determine if it should use local meshes or external Internet communications to reach other robots or the Internet.
In addition, since the information being exchanged between robots may affect critical systems and prevent crashes and other dangerous behavior, the communications should use either redundant technology (several Wi-Fi cards, or a variety of communication tech – satellite, Bluetooth, UHF/VHF, 4G/LTE, etc.
The last, and perhaps most troublesome, is the fear people have of the robot revolution, Many people in manufacturing are afraid of losing their jobs, and people are becoming downright afraid to even imagine a future with robots as core enabling technology.
The drones for military missions face additional challenges
Originally designed by Massachusetts Institute of Technology engineering students, the Perdix drone was modified for military use by the scientists and engineers of MIT Lincoln Laboratory starting in 2013. Drawing inspiration from the commercial smartphone industry, Perdix software and hardware has been continually updated in successive design generations. Now in its sixth generation, October’s test confirmed the reliability of the current all-commercial-component design under potential deployment conditions—speeds of Mach 0.6, temperatures of minus 10 degrees Celsius, and large shocks—encountered during ejection from fighter flare dispensers.
“The key is a modular UAV that can easily accept different payloads depending on which missions are desired and can be produced cheaply enough that they are one-way.” Adaptability is important because different payloads are required for different types of mission: the drones may be equipped with video cameras or other sensors, jammers to interfere with enemy radar or they might carry explosive warheads for kamikaze-style attacks. In defensive mode, a swarm can form a protective cordon against fleets of fast boats like those used by Iran’s Revolutionary Guard. The swarm might carry out high-risk reconnaissance missions, collecting imagery or other data from targets too well-defended for a Predator drone or a manned aircraft to approach, explains Lee Mastroianni, project manager of LOCUST.
Combat zone is a lot more chaotic than a construction site or a quiet patch of sky. For a robotic swarm to work effectively, it has to respond not only to missiles whizzing around but electronic attacks on its communications and GPS.
At the tail end of last year DARPA announced it had done exactly that, using its Collaborative Operations in Denied Environment (CODE) project to equip a squad of drones with the ability to “adapt and respond to unexpected threats” high above the Arizona desert, even after human communication was knocked out.
Managing the swarm requires a new approach to control: instead of remotely piloting a single drone, the operator manages the swarm. He describes how the operator’s interface will handle “aggregation” and “disaggregation”, his terms for drones joining or leaving the swarm. A single drone might detach to get a closer look at a target, and return or carry out an attack.
Battery life is a big issue for small drones. But a swarm can have a “hive”, a base station where individual drones return for recharging while the rest continue their mission. To the operator, unaware of charging going on in the background, the swarm’s endurance is unlimited. This approach is relatively easy for fixed bases; Stephen Crampton, CEO of Swarm Systems says a mobile hive for soldiers on patrol is more challenging.
Mastroianni says the biggest challenges for the swarm are not technical, but more based on perception: safety policies treat unmanned aircraft as if they are manned, meaning that they are highly regulated. “Establishing trust in autonomous UAV systems is not only the biggest challenge, but a major objective,” Mastroianni says. Swarms at sea are a start, but the real impact will be when they engage in land warfare. Stephen Crampton, CEO of Swarm Systems, says the cluttered environment where drones have to avoid trees, buildings and power lines is far more difficult than open water. Autonomous sense-and-avoid for small drones is still in its early stages, but as processors get more powerful, it is becoming more reliable. Crampton says that other advances such as deep learning and neural networks also offer potential solutions and the technology is advancing rapidly.
Recent successful demonstrations indicate that Swarm challenges are being overcome by advances in computer science, artificial intelligence, cognitive and behavioral sciences, machine training and learning, and communication technologies. Collaborative autonomy is an extension of autonomy that enables a team of unmanned systems to coordinate their activities to achieve common goals without human oversight. Autonomously coordinated unmanned systems may be capable of faster, more synchronized fire and maneuver than would be possible with remotely controlled assets. This trend will lead to a shift toward strategic decision making for a team of vehicles and away from direct control of any single vehicle.
Technological developments will enable new capabilities in small UAVs in the future. Advances in processing technology will enable the inclusion of increasingly sophisticated artificial intelligence and greater degrees of autonomy. These developments will have significant implications, enabling small UAVs to evade existing jamming technology and potentially carry out autonomous targeting.
Intel also produces chip-scale neural network hardware, such as the Movidius, which is the ‘brain’ of the popular DJI Phantom 4. In January 2018, Intel demonstrated a palm-sized consumer quadcopter retailing at just $99 with a Movidius processor. The technology will continue to get smaller and more capable. Qualcomm Technologies, which makes the processors in most of the world’s smartphones, also offers neural hardware. Their credit-card-sized Qualcomm Flight is aimed at the UAV market. In particular it tackles the challenge of ‘simultaneous location and mapping’ or SLAM, where a robot creates a map of its surroundings from video imagery as it goes.
SLAM allows UAVs to navigate by sight alone. SLAM is important because most UAVs rely on GPS to navigate and find their way to a target, and some jammers work by blocking the satellite navigation signal. A UAV using visual guidance can find its way just as well without satellite assistance, making such jammers ineffective. Equally importantly, SLAM will enable UAVs to find their way around the inside of buildings. The PD-100 Black Hornet used by several militaries is already advertised as being capable of operating inside structures.
Deep learning also allows UAVs to identify objects automatically. A number of applications of this capability have already been demonstrated in the commercial sector. Similar technology could allow a small UAV to locate and identify military targets—vehicles, artillery or personnel wearing a specific uniform or carrying weapons. The US military is developing deep learning technology to enable small UAVs to locate and identify targets.
Small, low-cost UAVs capable of autonomous route planning and obstacle avoidance, navigation and target identification would have tremendous military potential. Without a need for a link to a human operator they could autonomously verify and attack targets. Previously there has always been a desire by the military to maintain a ‘man-in-the-loop’ controlling any autonomous system. More recently this has been adapted to ‘man-on-the loop’ in which a human is not directly in charge but can step in at any point.
The Navy Wants Swarm to scavenge power directly from the battlefield
The problem is that future conflicts are likely to feature clouds of small drones, whether operating in swarms to overwhelm an enemy, or a mini-drone carried in a soldier’s pocket that flies ahead to scout out a building. But tiny drones have tiny batteries measured in thirty minutes or so of flight, and the battlefield is not the place to search for an electrical outlet to recharge.
However the Urban environment would allow a drone “to ‘dock’ on a power line in an urban environment, scavenging magnetic energy as a means to trickle-charge its onboard batteries prior to mission continuation. “The infrastructure to manage a future fleet of sUAS [small UAVs] in the field under austere conditions may be daunting considering the magnitude of battery recharging needs,” the navy notes. “It is also desirable to simultaneously increase mission duration and persistence; therefore, the ability to scavenge power directly from the battlefield would be an important military technology with other dual-use civilian applications.” “If the energy scavenging source is collocated at the mission area, full mission persistence might be achieved and the micro- and small UAS may never need to return to base.”
Remarkable is the amount of energy that’s floating around a battlefield. “The types of energy harvesting that fall into this category are broad, and include vibrational energy, simple mechanical energy, and electromagnetic energy,” says the navy. “Sources of electromagnetic energy that is abundant and available for harvesting and conversion include high-voltage substations, transformers, and alternating current transmission line (i.e., power lines).”
A team of autonomous quadcopters can now work together without crashing.
One of the challenge for implementing large swarm of drones is avoiding crashes. Even gentle touching or getting in the airflow of another quadcopter lead them to crash. But now, researchers at Georgia Institute of Technology have found a way to fix this by implementing a “barrier certificate” around each quadcopter. It works like a forcefield that rejects any other quadcopter that gets too close. As soon as one quadcopter flies within range, it reroutes to move away and continues peacefully on its way.
While this combats the collision problem, researchers also had to solve the air flow problem. They gave each quadcopter a two feet tall “top hat” to make sure they can’t undercut another quadcopter and mess with its air flow. “Safety bubbles” and “top hats” together now allow groups of quadcopters to swarm without the aid of human operators. So now instead of worrying about just one rogue quadcopter, we can worry about entire teams of them.
Textron’s Synturian family of multi-vehicle control and collaboration technologies
The Synturian family of products includes two main product lines: Synturian Control and Synturian Remote. Synturian Control is a multi-platform, multi-vehicle, multi-domain control system that enhances collaboration and dissemination of information. Synturian Remote includes mobile, network-strengthened tools that enhance situational awareness through timely information and collaboration.
The Textron systems can control multiple aircraft, ground and maritime and vessels or vehicles at a onetime including Army Shadow, Hunter and Gray Eagle Unmanned Aerial System (UAS). The Textron systems is compliant with NATO standardization agreement (STANAG) 4586 and configurable with the S-788, S-280 and Conex shelters as well as shipboard environments.
The Textron control station features are command and control, payload control and weapons control capabilities. Scalable, modular and intuitive, the Synturian system delivers situational understanding to the point of action. Built around a service-oriented architecture for rapid capability integration, users can access new capabilities with plugand-play simplicity through the universal interface. This gives users the same experience across controlled assets, with a map-centric view that brings mission information forward while platform status is automated in the background. Synturian Remote has successfully demonstrated its remote terminal capabilities with Shadow, Aerosonde, and Textron Aviation’s special missions platforms.
The iCommand suite is a battlespace management system that links people, platforms and payloads in a real-time and highly intuitive, integrated experience. iCommand is a Integrated Command Suite which delivers superior command and control technology. ICommand harnesses real time data fusion to provide synchronized C2 across manned and unmanned systems, unparalleled operational pictures for decision makers and provide touch screen speed for contingency planning, decision making and asset management. The iCommand suite links people, platforms and payloads in real time.
The RemoteView Pro is comprehensive imagery analysis capabilities which can quickly find, interpret and annotate items of interest. The RemoteView Pro includes toolsets for imager and multi-image analysis, centric graphical user interface (GUI) and customizable streamlined navigation and workflow-aligned toolbars and profiles. The Unmanned Aerial Vehicle (UAV), Ground and Maritime collects imagery and information, the RemoteView software allows tactical teams to interpret and analyze the information collected.
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