In this paper, we investigate the integration of drone identification data (Remote ID) with collision avoidance mechanisms to improve the safety and efficiency of multi-drone operations. We introduce an improved Near Mid-Air Collision (NMAC) definition, termed as UAV NMAC (uNMAC), which accounts for uncertainties in the drone's location due to self-localization errors and possible displacements between two location reports. Our proposed uNMAC-based Reciprocal Velocity Obstacle (RVO) model integrates Remote ID messages with RVO to enable enhanced collision-free navigation. We propose modifications to the Remote ID format to include data on localization accuracy and drone airframe size, facilitating more efficient collision avoidance decisions. Through extensive simulations, we demonstrate that our approach halves mission execution times compared to a conservative standard Remote ID-based RVO. Importantly, it ensures collision-free operations even under localization uncertainties. By integrating the improved Remote ID messages and uNMAC-based RVO, we offer a solution to significantly increase airspace capacity while adhering to strict safety standards. Our study emphasizes the potential to augment the safety and efficiency of future drone operations, thereby benefiting industries reliant on drone technologies.

Ukrainian officials are generally tight-lipped about attacks inside Russia, says BBC World Affairs correspondent Paul Adams. But it seems that as the campaign gathers pace, officials in Kyiv are more willing to claim them as part of the country's war effort.

Two Ukrainian drones attacked the Russian town of Kurchatov in the Kursk region, damaging administrative and residential buildings, while a third drone was shot down near Moscow, local officials said. Kursk regional Governor Roman Starovoit said emergency services were assessing the damage in Kurchatov town following the early morning attack on Friday. Starovoit wrote on the Telegram messaging app that two buildings were damaged but did not provide further details. Moscow mayor Sergei Sobyanin also reported early on Friday that Russian air defences had shot down a drone that was approaching the capital city. The drone was downed near Lyubertsy, which is located approximately 20km (12 miles) southeast of central Moscow, he wrote on Telegram.

The New York Police department has been using drones in a limited capacity for years -- deploying unmanned aircraft systems for search and rescue missions, to document crime scenes, or to monitor large public events like New Years Eve in Times Square. Soon, you might see one in your backyard as well: NYPD officials have announced plans to use drones to follow up on noise complaints during the long Labor Day weekend. "If a caller states there is a large crowd, a large party in a backyard, we're going to be utilizing our assets to go up and check on the party," Assistant NYPD Commissioner Kaz Daughtry said during a press conference Thursday. Privacy advocates have been quick to respond, with a representative from the New York Civil Liberties Union telling the Associated Press that the announcement "flies in the face of the POST Act" that requires police to publish its use policies for surveillance technology. And indeed, the plan could represent a stark departure from those policies.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Ukraine told critics of the pace of its three-month-old counteroffensive to "shut up" on Thursday, the sharpest signal yet of Kyiv's frustration at leaks from Western officials that say its forces are advancing too slowly. Nearly three months since launching a much vaunted counteroffensive using hundreds of billions of dollars of Western military equipment, Ukraine has recaptured more than a dozen villages but has yet to penetrate Russia's main defences. Stories in the New York Times, Washington Post and other news organisations last week quoted U.S. and other Western officials as suggesting the offensive was falling short of expectations.

Ukrainian officials are generally tight-lipped about attacks inside Russia. But it seems that as the campaign gathers pace, officials in Kyiv seem more willing to claim them as part of the country's war effort.

Rep. Mike Gallagher, R-Wis., tells'America Reports' that China is the primary geopolitical threat to the U.S. and should be addressed more by presidential candidates. The tentacles of the Chinese Communist Party (CCP) are creeping into an increasing number of U.S. industries in China's coordinated campaign to infiltrate critical industries to the U.S. economy. The CCP views theft of U.S. intellectual property as "a strategic resource," and China remains the largest source of counterfeit and pirated goods in the world. Chinese companies are building electric vehicle (EV) battery plants near key U.S. military installations, and China still controls the global chips market despite investments in U.S. production. China is also flexing its dominance of the rare earth sector in retaliation for U.S. trade policy, and China is in talks to create a new military facility just miles from the American homeland.

This work presents a study on parallel and distributional deep reinforcement learning applied to the mapless navigation of UAVs. For this, we developed an approach based on the Soft Actor-Critic method, producing a distributed and distributional variant named PDSAC, and compared it with a second one based on the traditional SAC algorithm. In addition, we also embodied a prioritized memory system into them. The UAV used in the study is based on the Hydrone vehicle, a hybrid quadrotor operating solely in the air. The inputs for the system are 23 range findings from a Lidar sensor and the distance and angles towards a desired goal, while the outputs consist of the linear, angular, and, altitude velocities. The methods were trained in environments of varying complexity, from obstacle-free environments to environments with multiple obstacles in three dimensions. The results obtained, demonstrate a concise improvement in the navigation capabilities by the proposed approach when compared to the agent based on the SAC for the same amount of training steps. In summary, this work presented a study on deep reinforcement learning applied to mapless navigation of drones in three dimensions, with promising results and potential applications in various contexts related to robotics and autonomous air navigation with distributed and distributional variants.

Cellular-connected unmanned aerial vehicles (UAVs) have gained increasing attention due to their potential to enhance conventional UAV capabilities by leveraging existing cellular infrastructure for reliable communications between UAVs and base stations. They have been used for various applications, including weather forecasting and search and rescue operations. However, under extreme weather conditions such as rainfall, it is challenging for the trajectory design of cellular UAVs, due to weak coverage regions in the sky, limitations of UAV flying time, and signal attenuation caused by raindrops. To this end, this paper proposes a physics-based trajectory design approach for cellular-connected UAVs in rainy environments. A physics-based electromagnetic simulator is utilized to take into account detailed environment information and the impact of rain on radio wave propagation. The trajectory optimization problem is formulated to jointly consider UAV flying time and signal-to-interference ratio, and is solved through a Markov decision process using deep reinforcement learning algorithms based on multi-step learning and double Q-learning. Optimal UAV trajectories are compared in examples with homogeneous atmosphere medium and rain medium. Additionally, a thorough study of varying weather conditions on trajectory design is provided, and the impact of weight coefficients in the problem formulation is discussed. The proposed approach has demonstrated great potential for UAV trajectory design under rainy weather conditions.

Debris rained from the Kyiv night sky as Russia launched air attacks on early Wednesday, killing at least two people in the Ukrainian capital, Mayor Vitali Klitschko wrote on the Telegram messaging app. Ukraine and Russia made their boldest drone and missile strikes in months on each other, with a strike in Kyiv killing two people while a strike on ships in the Black Sea and an airport near the border lasted for hours, according to local reports. "While the Russians have been retaliating brutally against Ukraine, Kyiv's incremental escalation has prevented a massive conventional (or nuclear attack) that would have obliterated Ukraine," Rebekah Koffler, president of Doctrine & Strategy Consulting and a former Defense Intelligence Agency officer, told Fox News Digital. "It's quite witty," she said. "Will this win the war for Ukraine? But it might gradually wear down the Russian people's morale."