Russian President Vladimir Putin appears uninterested in peace in Ukraine, and there is no end to the war in sight. Kyiv has increasingly reached the conclusion that the country must do all it can to guarantee its own security. The Russians have yet again shifted their tactics, says Sokil. Several months ago, they would send small units into battle, but now, it is often just single soldiers operating on their own. And they are no longer looking to fight, preferring instead to just sneak forward and wait for air support, says the Ukrainian major. Their FPV drones are everywhere," he says, using the common shorthand for first-person view." On a mild, late summer night, Sokil is resting at a farm on the western edge of the Donbas, taking a drag from his cigarette.

Existing decentralized methods for multi-agent motion planning lack formal, infinite-horizon safety guarantees, especially for communication-constrained systems. We present R3R, to our knowledge the first decentralized and asynchronous framework for multi-agent motion planning under distance-based communication constraints with infinite-horizon safety guarantees for systems of nonlinear agents. R3R's novelty lies in combining our gatekeeper safety framework with a geometric constraint called R-Boundedness, which together establish a formal link between an agent's communication radius and its ability to plan safely. We constrain trajectories to within a fixed planning radius that is a function of the agent's communication radius, which enables trajectories to be shown provably safe for all time, using only local information. Our algorithm is fully asynchronous, and ensures the forward invariance of these guarantees even in time-varying networks where agents asynchronously join, leave, and replan. We validate our approach in simulations of up to 128 Dubins vehicles, demonstrating 100% safety in dense, obstacle rich scenarios. Our results demonstrate that R3R's performance scales with agent density rather than problem size, providing a practical solution for scalable and provably safe multi-agent systems.

This paper presents a nonlinear integrated guidance and control (IGC) approach for flexible leader-follower formation flight of fixed-wing unmanned aerial vehicles (UAVs) while accounting for high-fidelity aerodynamics and thrust dynamics. Unlike conventional leader-follower schemes that fix the follower's position relative to the leader, the follower is steered to maintain range and bearing angles (which is the angle between its velocity vector and its line-of-sight (LOS) with respect to the leader) arbitrarily close to the prescribed values, enabling the follower to maintain formation on a hemispherical region behind the leader. The proposed IGC framework directly maps leader-follower relative range dynamics to throttle commands, and the follower's velocity orientation relative to the LOS to aerodynamic control surface deflections. This enables synergism between guidance and control subsystems. The control design uses a dynamic surface control-based backstepping approach to achieve convergence to the desired formation set, where Lyapunov barrier functions are incorporated to ensure the follower's bearing angle is constrained within specified bounds. Rigorous stability analysis guarantees uniform ultimate boundedness of all error states and strict constraint satisfaction in the presence of aerodynamic nonlinearities. The proposed flexible formation scheme allows the follower to have an orientation mismatch relative to the leader to execute anticipatory reconfiguration by transitioning between the relative positions in the admissible formation set when the leader aggressively maneuvers. The proposed IGC law relies only on relative information and onboard sensors without the information about the leader's maneuver, making it suitable for GPS-denied or non-cooperative scenarios. Finally, we present simulation results to vindicate the effectiveness and robustness of our approach.

European Union chief Ursula von der Leyen calls for action against Russian hybrid warfare after drones and warplanes violated six European nations' airspace in two weeks.

Three killed in latest Ukrainian strike on Russia's Belgorod region Three people have been killed and at least nine others injured in Ukraine's latest attack on the Russian border region of Belgorod, according to its governor, Vyacheslav Gladkov. The deaths happened following a strike on the village of Maslova Pristan early on Wednesday, Gladkov said. Emergency workers were continuing to search for people feared trapped under rubble. It is the third consecutive day that Ukraine has struck the region, leaving thousands of people without power and at least two other people dead. Ukraine has not commented on the attacks but has repeatedly struck targets inside Russia, including Belgorod, during the conflict, which is now in its fourth year.

Can Ukraine restore its pre-war borders? Why are Tomahawk missiles for Ukraine a'red line' for Russia? Is Russia testing NATO with aerial incursions in Europe? Russian President Vladimir Putin said his forces have captured almost 5,000 square kilometres (1,930sq miles) of Ukrainian territory so far this year, and Moscow retains the strategic initiative on the battlefield. Russian troops have captured the Ukrainian villages of Novovasylivka in the southeastern Zaporizhia region and Fedorivka in the eastern Donetsk region, Russia's defence ministry said.

The National Police Agency held its first expert panel meeting on Tuesday on countering illegal drone flights amid rising concerns over their potential use in terrorism and other threats. The National Police Agency on Tuesday held the first meeting of an expert panel on measures against illegal drone flights, in light of the growing threat of drones being used for terrorism and other purposes. The panel plans to compile a report by the end of the year on expanding the list of no-fly zones and penalties, with a view to revising the drone control law. The law was established in 2016 in the wake of an incident in which a drone fell on the roof of the Prime Minister's Office in Tokyo. It currently bans drone flights within about 300 meters of important facilities such as the National Diet Building, the Imperial Palace and nuclear power plants.

Onboard simultaneous localization and mapping (SLAM) methods are commonly used to provide accurate localization information for autonomous robots. However, the coordinate origin of SLAM estimate often resets for each run. On the other hand, UWB-based localization with fixed anchors can ensure a consistent coordinate reference across sessions; however, it requires an accurate assignment of the anchor nodes' coordinates. To this end, we propose a two-stage approach that calibrates and fuses UWB data and SLAM data to achieve coordinate-wise consistent and accurate localization in the same environment. In the first stage, we solve a continuous-time batch optimization problem by using the range and odometry data from one full run, incorporating height priors and anchor-to-anchor distance factors to recover the anchors' 3D positions. For the subsequent runs in the second stage, a sliding-window optimization scheme fuses the UWB and SLAM data, which facilitates accurate localization in the same coordinate system. Experiments are carried out on the NTU VIRAL dataset with six scenarios of UAV flight, and we show that calibration using data in one run is sufficient to enable accurate localization in the remaining runs. We release our source code to benefit the community at https://github.com/ntdathp/slam-uwb-calibration.

Abstract-- Artificial Potential Field (APF) methods are widely used for reactive flocking control, but they often suffer from challenges such as deadlocks and local minima, especially in the presence of obstacles. Existing solutions to address these issues are typically passive, leading to slow and inefficient collective navigation. As a result, many APF approaches have only been validated in obstacle-free environments or simplified, pseudo-3D simulations. This paper presents GO-Flock, a hybrid flocking framework that integrates planning with reactive APF-based control. GO-Flock consists of an upstream Perception Module, which processes depth maps to extract waypoints and virtual agents for obstacle avoidance, and a downstream Collective Navigation Module, which applies a novel APF strategy to achieve effective flocking behavior in cluttered environments. We evaluate GO-Flock against passive APF-based approaches to demonstrate their respective merits, such as their flocking behavior and the ability to overcome local minima. Finally, we validate GO-Flock through obstacle-filled environment and also hardware-in-the-loop experiments where we successfully flocked a team of nine drones--six physical and three virtual-- in a forest environment. I. INTRODUCTION Flocking behavior, commonly observed in nature, involves the collective and coordinated movement of groups, such as flocks of birds or schools of fish.

Use BBC.com or the new BBC App to listen to BBC podcasts, Radio 4 and the World Service outside the UK. Is Russia using my childhood home as a military base? Vitaly's home village of Verkhnya Krynytsya in the Zaporizhzhia region was occupied by Russia shortly after the start of the full-scale invasion in February 2022. Now, in a Ukrainecast exclusive, he tells Victoria why it's likely his childhood home is being used as a base by the Russian military. Plus, BBC Verify has revealed a surge in Ukrainian drone strikes on Russian oil refineries in recent months.