It's possible to distribute the Internet to users via drones. However it is then necessary to place the drones according to the positions of the users. Moreover, the 5th Generation (5G) New Radio (NR) technology is designed to accommodate a wide range of applications and industries. The NGNM 5G White Paper \cite{5gwhitepaper} groups these vertical use cases into three categories: - enhanced Mobile Broadband (eMBB) - massive Machine Type Communication (mMTC) - Ultra-Reliable Low-latency Communication (URLLC). Partitioning the physical network into multiple virtual networks appears to be the best way to provide a customised service for each application and limit operational costs. This design is well known as \textit{network slicing}. Each drone must thus slice its bandwidth between each of the 3 user classes. This whole problem (placement + bandwidth) can be defined as an optimization problem, but since it is very hard to solve efficiently, it is almost always addressed by AI in the litterature. In my internship, I wanted to prove that viewing the problem as an optimization problem can still be useful, by building an hybrid solution involving on one hand AI and on the other optimization. I use it to achieve better results than approaches that use only AI, although at the cost of slightly larger (but still reasonable) computation times.

You're about to experience the level of shock and awe usually reserved for lottery winners and people who find 20 bills on the sidewalk. We're talking about a BOGO drone deal so good you'll think we're pulling your leg. When you buy the Ninja Dragon Phantom Eagle PRO drone for 139.99, you'll get the Ninja Blade K for free (a 299.99 value!). That's less than the price of a decent pair of sneakers these days, and these drones are quite a bit more fun than walking. It doesn't matter--both quadcopters are easy for beginners, even kids, to fly.

Russia started producing a new long-range attack drone called the Garpiya-A1 last year using Chinese engines and parts, which it has deployed in the war in Ukraine, according to two sources from a European intelligence agency and documents seen by Reuters. The intelligence -- which included a production contract for the new drone, company correspondence on the manufacturing process and financial documents -- indicated that IEMZ Kupol, a subsidiary of Russian state-owned weapons-maker Almaz-Antey, produced more than 2,500 Garpiyas from July 2023 to July 2024. The existence of the new Russian drone incorporating Chinese technology has not been previously reported. IEMZ Kupol and Almaz-Antey did not respond to requests for comment. The two intelligence sources said that the Garpiya, which means Harpy in Russian, has been deployed against military and civilian targets in Ukraine, causing damage to critical infrastructure as well as both civilian and military casualties.

The question of how cyber-physical systems should interact with human partners that can take over control or exert oversight is becoming more pressing, as these systems are deployed for an ever larger range of tasks. Drawing on the literatures on handing over control during semi-autonomous driving and human-robot interaction, we propose a design of a take-over request that combines an abstract pre-alert with an informative TOR: Relevant sensor information is highlighted on the controller's display, while a spoken message verbalizes the reason for the TOR. We conduct our study in the context of a semi-autonomous drone control scenario as our testbed. The goal of our online study is to assess in more detail what form a language-based TOR should take. Specifically, we compare a full sentence condition to shorter fragments, and test whether the visual highlighting should be done synchronously or asynchronously with the speech. Participants showed a higher accuracy in choosing the correct solution with our bi-modal TOR and felt that they were better able to recognize the critical situation. Using only fragments in the spoken message rather than full sentences did not lead to improved accuracy or faster reactions. Also, synchronizing the visual highlighting with the spoken message did not result in better accuracy and response times were even increased in this condition.

Obtaining reliable position estimation is fundamental for unmanned aerial vehicles during mission execution, especially in harsh environments. However, environmental interference and abrupt changes usually degrade measurement reliability, leading to estimation divergence. To address this, existing works explore adaptive adjustment of sensor confidence. Unfortunately, existing methods seldom include synchronous evaluation of estimation precision, thereby rendering adjustments sensitive to abnormal data and susceptible to divergence. To tackle this issue, we propose a ternary-channel adaptive evolving estimator equipped with an online error monitor, where the ternary channels, states, noise covariance matrices and especially aerial drag evolve simultaneously with the environment. Firstly, an augmented filter is employed to pre-process multidimensional data, followed by an inverse-Wishart smoother utilized to obtain posterior states and covariance matrices. Error propagation relation during estimation is analyzed, and hence, an indicator is devised for online monitoring estimation errors. Under this premise, several restrictions are applied to suppress potential divergence led by interference. Additionally, considering motion dynamics, the aerial drag matrix is reformulated based on updated states and covariance matrices. Finally, the observability, numerical sensitivity and arithmetic complexity of the proposed estimator are mathematically analyzed. Extensive experiments are conducted in both common and harsh environments (with average RMSE 0.17m and 0.39m respectively) to verify adaptability of algorithm and effectiveness of restriction design, which shows our method outperforms the state-of-the-art.

Despite this reputation among rank-and-file service members--and maybe because of it--Flash has also become a source of some controversy among the upper echelons of Ukraine's military, he tells me. The Armed Forces of Ukraine declined multiple requests for comment, but Flash and his colleagues claim that some high-ranking officials perceive him as a security threat, worrying that he shares too much information and doesn't do enough to secure sensitive intel. As a result, some refuse to support or engage with him. Others, Flash says, pretend he doesn't exist. Either way, he believes they are simply insecure about the value of their own contributions--"because everybody knows that Serhii Flash is not sitting in Kyiv like a colonel in the Ministry of Defense," he tells me in the abrasive fashion that I've come to learn is typical of his character.

Iran's Foreign Minister Abbas Araghchi condemned allegations by Western countries that Tehran has supplied ballistic missiles to Russia for use against Ukraine, claiming that the US and its allies were acting on "faulty intelligence". He called the US, the UK, France and Germany "sanctions addicts", referring to announcements on Tuesday that they would be punishing the alleged transfers of missiles to Russia with sanctions, including on national carrier Iran Air. Lammy said during his trip to Kyiv that the UK would provide "hundreds of additional air defence missiles, tens of thousands of additional artillery ammunition rounds and more armoured vehicles to Ukraine by the end of the year". Lithuania's Defence Minister Laurynas Kasciunas said NATO aircraft based in the Baltic states should shoot down Russian drones that drift into their airspace after a Russian drone crashed in Latvia last week. NATO aircraft "must not only patrol but also, if necessary, if possible destroy the drones," he said.

In this study, we conduct a comprehensive benchmark of the Safe Reinforcement Learning (Safe RL) algorithms for the task of vision-driven river following of Unmanned Aerial Vehicle (UAV) in a Unity-based photo-realistic simulation environment. We empirically validate the effectiveness of semantic-augmented image encoding method, assessing its superiority based on Relative Entropy and the quality of water pixel reconstruction. The determination of the encoding dimension, guided by reconstruction loss, contributes to a more compact state representation, facilitating the training of Safe RL policies. Across all benchmarked Safe RL algorithms, we find that First Order Constrained Optimization in Policy Space achieves the optimal balance between reward acquisition and safety compliance. Notably, our results reveal that on-policy algorithms consistently outperform both off-policy and model-based counterparts in both training and testing environments. Importantly, the benchmarking outcomes and the vision encoding methodology extend beyond UAVs, and are applicable to Autonomous Surface Vehicles (ASVs) engaged in autonomous navigation in confined waters.

In this paper, we consider the tracking of arbitrary curvilinear geometric paths in three-dimensional output spaces of unmanned aerial vehicles (UAVs) without pre-specified timing requirements, commonly referred to as path-following problems, subjected to bounded inputs. Specifically, we propose a novel nonlinear path-following guidance law for a UAV that enables it to follow any smooth curvilinear path in three dimensions while accounting for the bounded control authority in the design. The proposed solution offers a general treatment of the path-following problem by removing the dependency on the path's geometry, which makes it applicable to paths with varying levels of complexity and smooth curvatures. Additionally, the proposed strategy draws inspiration from the pursuit guidance approach, which is known for its simplicity and ease of implementation. Theoretical analysis guarantees that the UAV converges to its desired path within a fixed time and remains on it irrespective of its initial configuration with respect to the path. Finally, the simulations demonstrate the merits and effectiveness of the proposed guidance strategy through a wide range of engagement scenarios, showcasing the UAV's ability to follow diverse curvilinear paths accurately.

French authorities foiled three plots to attack the Olympic and Paralympic Games in Paris and other cities that hosted this year's events, the national counterterrorism prosecutor has said. Olivier Christen said on Wednesday the plots included plans to attack "Israeli institutions or representatives of Israel in Paris" during the July 26 – August 11 Olympic competition. The prosecutor told broadcaster France Info that "the Israeli team itself was not specifically targeted." He did not give further details. Five people, including a minor, were arrested on suspicion of involvement in the three foiled plots against the Summer Games, which were held against the backdrop of Israel's assault on Gaza and Russia's war in Ukraine.