Unmanned Aerial Vehicles (UAVs), although adept at aerial surveillance, are often constrained by limited battery capacity. By refueling on slow-moving Unmanned Ground Vehicles (UGVs), their operational endurance can be significantly enhanced. This paper explores the computationally complex problem of cooperative UAV-UGV routing for vast area surveillance within the speed and fuel constraints, presenting a sequential multi-agent planning framework for achieving feasible and optimally satisfactory solutions. By considering the UAV fuel limits and utilizing a minimum set cover algorithm, we determine UGV refueling stops, which in turn facilitate UGV route planning at the first step and through a task allocation technique and energy constrained vehicle routing problem modeling with time windows (E-VRPTW) we achieve the UAV route at the second step of the framework. The effectiveness of our multi-agent strategy is demonstrated through the implementation on 30 different task scenarios across 3 different scales. This work offers significant insight into the collaborative advantages of UAV-UGV systems and introduces heuristic approaches to bypass computational challenges and swiftly reach high-quality solutions.

Russia's defence ministry said that at least three Ukrainian drones were shot down in the latest attempt by Kyiv to attack sites in Moscow. The ministry said early on Tuesday that air defence systems destroyed two drones over the Kaluga and Tver regions, which border the Moscow region. A third drone was shot down closer to the Russian capital, over the Istra district of the Moscow region, it added. Moscow's Mayor Sergei Sobyanin said the "attack drones which targeted Moscow" were destroyed, according to Russia's TASS news agency. Sobyanin said on the Telegram messaging app that there had been "no casualties", according to initial information.

Russia launched a drone attack on Ukraine's Danube River port of Izmail, leading to widespread damage to infrastructure, according to the region's governor. The attack came hours ahead of talks between Russian President Vladimir Putin and his Turkish counterpart, Recep Tayyip Erdogan, which were expected to touch on ways to revive the Black Sea grain deal that Moscow abandoned in July. Ukraine and Romania disagreed over whether the attack on Izmail hit Romanian territory on the other side of the river. Foreign Minister Dmytro Kuleba said Ukraine had visual evidence of the incident. Romanian Foreign Minister Luminita Odobescu condemned the "cynical" Russian attack on Ukrainian infrastructure but said no Russian drones or debris had fallen on Romanian territory.

In the era of 5G mobile communication, there has been a significant surge in research focused on unmanned aerial vehicles (UAVs) and mobile edge computing technology. UAVs can serve as intelligent servers in edge computing environments, optimizing their flight trajectories to maximize communication system throughput. Deep reinforcement learning (DRL)-based trajectory optimization algorithms may suffer from poor training performance due to intricate terrain features and inadequate training data. To overcome this limitation, some studies have proposed leveraging federated learning (FL) to mitigate the data isolation problem and expedite convergence. Nevertheless, the efficacy of global FL models can be negatively impacted by the high heterogeneity of local data, which could potentially impede the training process and even compromise the performance of local agents. This work proposes a novel solution to address these challenges, namely personalized federated deep reinforcement learning (PF-DRL), for multi-UAV trajectory optimization. PF-DRL aims to develop individualized models for each agent to address the data scarcity issue and mitigate the negative impact of data heterogeneity. Simulation results demonstrate that the proposed algorithm achieves superior training performance with faster convergence rates, and improves service quality compared to other DRL-based approaches.

Both the image and the video show a fireball rising over a forested riverbank at night, but the visual evidence is of very low quality, in part because it was shot in the dark, from a distance, and in part because it is low-resolution. Additionally, the video appears to have been blurred in places, obscuring certain details.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A drone attack on a police headquarters in a major border town in eastern Burma has killed at least five officials including a senior army officer and a district administrator, members of two emergency rescue teams and media reports said Monday. The attack, carried out Sunday evening in two stages, is believed to be the deadliest aerial bombing targeting high-ranking security and administrative officials since armed resistance was launched more than two years ago against the military that seized power in February 2021 from the elected government of Aung San Suu Kyi. The takeover was met with peaceful nationwide protests, but after security forces cracked down with lethal force, many local armed resistance groups were formed and loosely organized into what is called the People's Defense Force, or PDF. It's the armed wing of Burma's shadow National Unity Government, which views itself as a country's legitimate administrative body.

This paper describes gaps in acquisition of drone imagery that impair the use with computer vision/machine learning (CV/ML) models and makes five recommendations to maximize image suitability for CV/ML post-processing. It describes a notional work process for the use of drones in wilderness search and rescue incidents. The large volume of data from the wide area search phase offers the greatest opportunity for CV/ML techniques because of the large number of images that would otherwise have to be manually inspected. The 2023 Wu-Murad search in Japan, one of the largest missing person searches conducted in that area, serves as a case study. Although drone teams conducting wide area searches may not know in advance if the data they collect is going to be used for CV/ML post-processing, there are data collection procedures that can improve the search in general with automated collection software. If the drone teams do expect to use CV/ML, then they can exploit knowledge about the model to further optimize flights.

Data collected at Hurricane Ian (2022) quantifies the demands that small uncrewed aerial systems (UAS), or drones, place on the network communication infrastructure and identifies gaps in the field. Drones have been increasingly used since Hurricane Katrina (2005) for disaster response, however getting the data from the drone to the appropriate decision makers throughout incident command in a timely fashion has been problematic. These delays have persisted even as countries such as the USA have made significant investments in wireless infrastructure, rapidly deployable nodes, and an increase in commercial satellite solutions. Hurricane Ian serves as a case study of the mismatch between communications needs and capabilities. In the first four days of the response, nine drone teams flew 34 missions under the direction of the State of Florida FL-UAS1, generating 636GB of data. The teams had access to six different wireless communications networks but had to resort to physically transferring data to the nearest intact emergency operations center in order to make the data available to the relevant agencies. The analysis of the mismatch contributes a model of the drone data-to-decision workflow in a disaster and quantifies wireless network communication requirements throughout the workflow in five factors. Four of the factors-availability, bandwidth, burstiness, and spatial distribution-were previously identified from analyses of Hurricanes Harvey (2017) and Michael (2018). This work adds upload rate as a fifth attribute. The analysis is expected to improve drone design and edge computing schemes as well as inform wireless communication research and development.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The New York City Police Department announced plans to fly surveillance drones over the city this Labor Day weekend to monitor outdoor parties or barbecues following complaints about large gatherings. The decision was revealed during a security briefing addressing J'ouvert, an annual Caribbean festival marking the end of slavery in which thousands of people take to the streets of Brooklyn. Assistant NYPD Commissioner Kaz Daughtry said at a press conference Thursday that the drones will respond to "non-priority and priority calls."

The United States says it has seen notable military progress by Ukraine's forces fighting in the Zaporizhia region over the last 72 hours. Ukrainian troops achieved "some success against that second line of Russian defences", White House National Security Council spokesperson John Kirby said. A recent drone attack on an airport in northwestern Russia's Pskov region was carried out from within Russian territory, Ukraine's intelligence chief Kyrylo Budanov said. The Pskov regional governor said Russian air defence units had "neutralised an unidentified object" spotted flying over the region, just days after a wave of Ukrainian drones destroyed military planes parked at an airfield in the region. The United States says it has seen notable military progress by Ukraine's forces fighting in the Zaporizhia region over the last 72 hours.