Not too long ago, automated flying machines whizzing around the skies were concepts gracing the pages of science fiction novels. Today, drones are used and seen frequently. From capturing incredible aerial shots for documentaries, to inspecting large structures to spot potential weaknesses, drones have become invaluable tools. As the Wright brothers' first successful airplane evolved into the sophisticated aircraft we see today, the very first drones too, have evolved and improved – and are continuing to do so, thanks to artificial intelligence. AI is paving the way for a new generation of self-flying drones, which can carry out tasks without requiring a human operator.

China is selling its most advanced "fully autonomous" military drones with fears that it could lead to a bloodbath in the Middle East. The Asian superpower is reportedly selling AI-enhanced combat drones to the region, with potentially disastrous consequences. Prof Toby Walsh, of the University of NSW, in Australia, said: "They would be impossible to defend yourself against. "Once the shooting starts, every human on the battlefield will be dead." US Defence Sec Mark Esper has said that China is selling drones programmed to decide themselves who lives or dies. He told a conference on Artificial Intelligence: "As we speak, the Chinese government is already exporting some of its most advanced military aerial drones to the Middle East as it prepares to export its next generation stealth UAVs when those come online.

This week, amazing video showed protesters on the streets of Chile teaming up to bring down a police drone with what appear to be simple pocket lasers. The footage shows a huge group of people aiming around 40 or 50 green handheld lasers at a police drone hovering overhead. After about 20 seconds of being targeted by the communal green laser beam, the drone appears to malfunction and slowly falls toward the ground. Yet, as it descends out of the laser's line of sight, the drone appears to momentarily regain control, Around ten seconds later, protester re-aim their group laser at the drone and it finally drops all the way into the crowd. Just how pocket lasers were able to cause a drone to malfunction remains unclear.

The world's largest drone manufacturer has announced plans for a new smartphone app that lets users identify mysterious drones flying around their neighborhood. Developed by DJI, the Shenzhen based drone giant, the unnamed app is targeted for a release in early 2020 pending approval by government regulators. The app will have a range of around .6 miles using WiFi Aware, a new communication protocol that allows WiFi-enabled devices to communicate with one another. DJI announced the new app at the United Nations-sponsored Drone Enable conference in Montreal this week. 'We've created a remote identification solution that works with what people already have,' DJI's Brendan Schulman told Reuters.

Several companies are pushing the boundaries of what is possible. Hardware is becoming ever more sophisticated, reducing weight, improving flight times and bringing down prices. Last month DJI launched the Mavic Mini, a tiny 249-gram drone with a range of 4km that can shoot 2.7K video and fly for 30 minutes on a single battery. A feat of engineering and a measure of how far things have come in the last decade. October also saw the launch of another industry benchmark: Skydio's new drone, the Skydio 2. It's lighter, cheaper and more sophisticated than the original R1 – which is saying something.

MONTREAL, QUEBEC – China's DJI, the world's largest commercial drone maker, said on Wednesday it is developing technology that would allow the public to track the registrations of drones in flight using just a smartphone, amid a broader industry push to make such data available. SZ DJI Technology Co. Ltd. aims to roll out a free app in 2020, pending regulatory approval, that would allow its users for the first time to identify any modern drone with a phone, company executives told Reuters. The push for remote identification technology comes amid regulatory calls for greater oversight of drone flight, on fears that untraceable, unmanned aircraft could be used for spying or accidentally disrupt commercial flights. DJI, which has an estimated 70 percent market share according to industry analysts, demonstrated its drone-to-phone transmission app at the United Nations aviation agency's Drone Enable conference in Montreal. "We've created a remote identification solution that works with what people already have," said Brendan Schulman, vice president of policy and legal affairs at DJI.

The stunning aerial dance of UFO's that wowed audiences in Steven Speilberg's Close Encounters of the Third Kind has become a reality thanks to the drone. The small aerial vehicles may be a potential threat in some circumstances but they can be beautiful in others. A spectacular aerial art form continues to evolve as operators use lighted drones and computer algorithms to create animations in the sky. Intel's 2018 light show in Sacramento used 1500 drones to put on this stunning display.

This research spans academia, militaries (though it can be difficult to suss out the actual breakthroughs from government propaganda), and private enterprise. Perhaps the most well known privately-owned robotics developer is Boston Dynamics, makers of the Atlas. You may remember this bipedal robot from September when it showed off its uncanny parkour abilities, which the robot can pull off 80 percent of the time. The Atlas is able to move so fluidly thanks to a novel optimization algorithm that breaks down complex movements into smaller reference motions for its arms, torso, and legs. However, while Boston Dynamics' Big Dog was developed as a quadrupedal cargo carrier for military operations, the Atlas is strictly for use as an emergency first responder.

In this paper, we consider a platform of flying mobile edge computing (F-MEC), where unmanned aerial vehicles (UA Vs) serve as equipment providing computation resource, and they enable task offload-ing from user equipment (UE). We aim to minimize energy consumption of all the UEs via optimizing the user association, resource allocation and the trajectory of UA Vs. To this end, we first propose a Convex optimizAtion based Trajectory control algorithm (CA T), which solves the problem in an iterative way by using block coordinate descent (BCD) method. Then, to make the real-time decision while taking into account the dynamics of the environment (i.e., UA V may take off from different locations), we propose a deep Reinforcement leArning based Trajectory control algorithm (RA T). In RA T, we apply the Prioritized Experience Replay (PER) to improve the convergence of the training procedure. Different from the convex optimization based algorithm which may be susceptible to the initial points and requires iterations, RA T can be adapted to any taking off points of the UA Vs and can obtain the solution more rapidly than CA T once training process has been completed. Simulation results show that the proposed CA T and RA T achieve the similar performance and both outperform traditional algorithms. Liang, Kezhi and Nauman are with the Department of Computer and Informantion Science, Northumbria University, Newcastle upon Tyne, UK, NE1 8ST. Cunhua and Arumugam are with School of Electronic Engineering and Computer Science, Queen Mary University of London, E1 4NS, U.K. Wei is with National Mobile Communications Research Lab, Southeast University, China. I NTRODUCTION With the popularity of computationally-intensive tasks, e.g., smart navigation and augmented reality, people are expecting to enjoy more convenient life than ever before. However, current smart devices and user equipments (UEs), due to small size and limited resource, e.g., computation and battery, may not be able to provide satisfactory Quality of Service (QoS) and Quality of Experience (QoE) in executing those highly demanding tasks. Mobile edge computing (MEC) has been proposed by moving the computation resource to the network edge and it has been proved to greatly enhance UE's ability in executing computation-hungry tasks [1].