Drones could soon be forced to have electronic number plates so they can be tracked by police and security teams as they fly through the skies. The plans are part of new regulations being drawn up by the Government that would allow a drone's speed, location, height, take-off point to be tracked - as well as the operator's location. To collect the information, remote ID technology will be installed in the drones, working in a similar way to the automatic number plate recognition (ANPR) system used on cars, vans and lorries. The move comes amid growing concern that the UK's drone registration scheme is not being enforced properly, as well as fears that drones could be used by terrorists to cause serious harm or economic damage. According to the Civil Aviation Authority, anyone with a drone weighing more than 250g needs to pass a test and get a flyer ID from the authority.

As mini UAVs become increasingly useful in the civilian work domain, the need for a method for them to operate safely in a cluttered environment is growing, especially for fixed-wing UAVs as they are incapable of following the stop-decide-execute methodology. This paper presents preliminary research to design a reactive collision avoidance algorithm based on the improved definition of the repulsive forces used in the Artificial potential field algorithms to allow feasible and safe navigation of fixed-wing UAVs in cluttered, dynamic environments. We present simulation results of the improved definition in multiple scenarios, and we have also discussed possible future studies to improve upon these results.

In this paper we address the control problem of aerial cable suspended load transportation, using multiple Unmanned Aerial Vehicles (UAVs). First, the dynamical model of the coupled system is obtained using the Newton-Euler formalism, for "n" UAVs transporting a load, where the cables are supposed to be rigid and mass-less. The control problem is stated as a trajectory tracking directly on the load. To do so, a hierarchical control scheme is proposed based on the attractive ellipsoid method, where a virtual controller is calculated for tracking the position of the load, with this, the desired position for each vehicle along with their desired cable tensions are estimated, and used to compute the virtual controller for the position of each vehicle. This results in an underdetermined system, where an infinite number of drones' configurations comply with the desired load position, thus additional constrains can be imposed to obtain an unique solution. Furthermore, this information is used to compute the attitude reference for the vehicles, which are feed to a quaternion based attitude control. The stability analysis, using an energy-like function, demonstrated the practical stability of the system, it is that all the error signals are attracted and contained in an invariant set. Hence, the proposed scheme assures that, given well posed initial conditions, the closed-loop system guarantees the trajectory tracking of the desired position on the load with bounded errors. The proposed control strategy was evaluated in numerical simulations for three agents following a smooth desired trajectory on the load, showing good performance.

It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation. By putting UAM into practical future transportation, several benefits can be realized, i.e., (i) the total travel time of passengers can be reduced compared to traditional transportation and (ii) there is no environmental pollution and no special labor costs to operate the system because electric batteries will be used in UAM system. However, there are various dynamic and uncertain factors in the flight environment, i.e., passenger sudden service requests, battery discharge, and collision among UAMs. Therefore, this paper proposes a novel cooperative MADRL algorithm based on centralized training and distributed execution (CTDE) concepts for reliable and efficient passenger delivery in UAM networks. According to the performance evaluation results, we confirm that the proposed algorithm outperforms other existing algorithms in terms of the number of serviced passengers increase (30%) and the waiting time per serviced passenger decrease (26%).

From Saudi Arabia to Myanmar and Iraq to Ethiopia, more and more militaries across the world are stockpiling Chinese combat drones and deploying them on the battlefield. In Yemen, a Saudi-led coalition has dispatched the Chinese aircraft, also known as uncrewed aerial vehicles or UAVs, as part of a devastating air campaign that has killed more than 8,000 Yemeni civilians in the past eight years. In Iraq, authorities say they used Chinese drones to carry out more than 260 air raids against ISIL (ISIS) targets as of mid-2018, with a success rate of nearly 100 percent. In Myanmar, the military -- armed with Chinese drones -- has conducted hundreds of air attacks on civilians and ethnic armed groups opposed to its power grab two years ago, while in Ethiopia, Prime Minister Abiy Ahmed's fleet of Chinese, Iranian and Turkish drones was critical in helping his forces thwart a rebel march in 2021 that threatened to overthrow his government. Other buyers of China's combat drones -- aircraft that, in addition to intelligence gathering, can also fire air-to-surface missiles -- include Morocco, Egypt, Algeria, the United Arab Emirates (UAE), Pakistan and Serbia.

Urban air mobility is the new mode of transportation aiming to provide a fast and secure way of travel by utilizing the low-altitude airspace. This goal cannot be achieved without the implementation of new flight regulations which can assure safe and efficient allocation of flight paths to a large number of vertical takeoff/landing aerial vehicles. Such rules should also allow estimating the effective capacity of the low-altitude airspace for planning purposes. Path planning is a vital subject in urban air mobility which could enable a large number of UAVs to fly simultaneously in the airspace without facing the risk of collision. Since urban air mobility is a novel concept, authorities are still working on the redaction of new flight rules applicable to urban air mobility. In this study, an autonomous UAV path planning framework is proposed using a deep reinforcement learning approach and a deep deterministic policy gradient algorithm. The objective is to employ a self-trained UAV to reach its destination in the shortest possible time in any arbitrary environment by adjusting its acceleration. It should avoid collisions with any dynamic or static obstacles and avoid entering prior permission zones existing on its path. The reward function is the determinant factor in the training process. Thus, two different reward function compositions are compared and the chosen composition is deployed to train the UAV by coding the RL algorithm in python. Finally, numerical simulations investigated the success rate of UAVs in different scenarios providing an estimate of the effective airspace capacity.

As the world accelerates the transition to greening its transportation network, nearly every manufacturer is jumping on the bandwagon. This is especially true in China through domestic market models such as the $5,000 Wuling Mini EV, the joint venture between MG-owner SAIC and General Motors that has sold more than 500,000 cars in just three years and outsells Tesla on a monthly basis. However, some legacy manufacturers in the region are far behind and falling further back every day. The only way to stand out in the crowd is to be unique, often through collaborations with other local Chinese brands. DJI, the commercial drone company, recently teamed up with Baojun (also SAIC/GM-owned) to make the Kiwi mini EV, featuring their self-driving tech and festooned with DJI logos across its doors.

Engineered organs that could end transplant waiting lists, abortion pills on demand and mass-marketing military drones that will revolutionize warfare are among those listed on MIT Technology Review's 10 Breakthrough Technologies of 2023. The list also includes the use of CRISPR to edit away people's problems with high cholesterol by rewriting a sliver of their DNA, artificial intelligence that makes artwork and NASA's James Webb Space Telescope, which is set to remodel our knowledge of the cosmos. The 22nd annual list features critical technological advances predicted to change how we live and work fundamentally. MIT Technology Review, owned by the Massachusetts Institute of Technology, compiled the list of companies or institutions set to develop breakthroughs and when the public can expect these innovations. Mat Honan, editor-in-chief of MIT Technology Review, said: 'Our breakthrough technologies lists are fascinating snapshots of the evolution of big tech innovation breakthroughs.

Tehran, Iran – The European Parliament's approval of a resolution calling on the bloc to consider a "terrorist" designation for the Islamic Revolutionary Guard Corps (IRGC) has received strong condemnation from senior Iranian officials and commanders. On Thursday, the European Parliament overwhelmingly approved a resolution that calls on the European Union to recognise Iran's elite force and its subsidiaries, like the paramilitary Basij and the Quds Force, as "terrorist" organisations. It also condemned the Iranian government's response to the protests that have been taking place in the country since September, the executions linked to the protests, and drone sales to Russia, while also recommending sanctions against Supreme Leader Ayatollah Ali Khamenei, President Ebrahim Raisi and all IRGC-linked foundations. The EU is not obliged to enforce the resolution. While senior EU politicians have voiced their support for the resolution, it is not expected to be among new sanctions on dozens of Iranian individuals and entities expected to be approved by the bloc on Monday.

This paper proposes a novel methodology for addressing the simulation-reality gap for multi-robot swarm systems. Rather than immediately try to shrink or `bridge the gap' anytime a real-world experiment failed that worked in simulation, we characterize conditions under which this is actually necessary. When these conditions are not satisfied, we show how very simple simulators can still be used to both (i) design new multi-robot systems, and (ii) guide real-world swarming experiments towards certain emergent behaviors when the gap is very large. The key ideas are an iterative simulator-in-the-design-loop in which real-world experiments, simulator modifications, and simulated experiments are intimately coupled in a way that minds the gap without needing to shrink it, as well as the use of minimally viable phase diagrams to guide real world experiments. We demonstrate the usefulness of our methods on deploying a real multi-robot swarm system to successfully exhibit an emergent milling behavior.