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.

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? The UN's International Atomic Energy Agency (IAEA) said that "two rounds of shelling struck around 1.25 km" [less than a mile] from the perimeter of Ukraine's Zaporizhzhia Nuclear Power Plant on Monday afternoon. IAEA chief Rafael Grossi warned the attacks came as the plant has been running on emergency diesel generators for almost two weeks after losing its external power source.

Abstract-- We propose SketchPlan, a diffusion-based planner that interprets 2D hand-drawn sketches over depth images to generate 3D flight paths for drone navigation. SketchPlan comprises two components: a SketchAdapter that learns to map the human sketches to projected 2D paths, and DiffPath, a diffusion model that infers 3D trajectories from 2D projections and a first person view depth image. Our model achieves zero-shot sim-to-real transfer, generating accurate and safe flight paths in previously unseen real-world environments. T o train the model, we build a synthetic dataset of 32k flight paths using a diverse set of photorealistic 3D Gaussian Splatting scenes. We automatically label the data by computing 2D projections of the 3D flight paths onto the camera plane, and use this to train the DiffPath diffusion model. However, since real human 2D sketches differ significantly from ideal 2D projections, we additionally label 872 of the 3D flight paths with real human sketches and use this to train the SketchAdapter to infer the 2D projection from the human sketch. We demonstrate SketchPlan's effectiveness in both simulated and real-world experiments, and show through ablations that training on a mix of human labeled and auto-labeled data together with a modular design significantly boosts its capabilities to correctly interpret human intent and infer 3D paths. In real-world drone tests, SketchPlan achieved 100% success in low/medium clutter and 40% in unseen high-clutter environments, outperforming key ablations by 20-60% in task completion.

British microcomputers were among more than 100,000 foreign-made parts contained in Russian missiles and drones used in Sunday's deadly strikes on Ukraine, Volodymyr Zelensky has said. The Ukrainian president called for further effective sanctions after saying parts originating in allied countries including Germany, Japan and the US have been identified in Russian weapons. The Department for Business and Trade (DBT) said it had recently undertaken efforts to crack down on UK firms whose products have continued to make their way into Russia's military supply chain. We take reports of goods from UK companies being found in Russian weaponry incredibly seriously, a government spokesperson said. The spokesperson said the government had banned the export of thousands of goods to Russia including every battlefield item Ukraine has brought to our attention, adding that they have imposed the most the most severe package of sanctions. What are the sanctions on Russia and are they working?

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? Ukraine's Zelenskyy says Western parts found in Russian drones, missiles Ukrainian President Volodymyr Zelenskyy has alleged that drones and missiles fired by Russia against his country are filled with parts sourced from Western companies. In a social media post on Monday, Zelenskyy said the hundreds of weapons used in Russian attacks over the previous two nights contained tens of thousands of components produced by firms in the United States, United Kingdom, Germany, Switzerland, Japan, South Korea, the Netherlands, Taiwan and China.

Achieving precise lateral motion modeling and decoupled control in hover remains a significant challenge for tail-sitter Unmanned Aerial Vehicles (UAVs), primarily due to complex aerodynamic couplings and the absence of welldefined lateral dynamics. This paper presents a novel modeling and control strategy that enhances yaw authority and lateral motion by introducing a sideslip force model derived from differential propeller slipstream effects acting on the fuselage under differential thrust. The resulting lateral force along the body y-axis enables yaw-based lateral position control without inducing roll coupling. The control framework employs a YXZ Euler rotation formulation to accurately represent attitude and incorporate gravitational components while directly controlling yaw in the yaxis, thereby improving lateral dynamic behavior and avoiding singularities. The proposed approach is validated through trajectory-tracking simulations conducted in a Unity-based environment. Tests on both rectangular and circular paths in hover mode demonstrate stable performance, with low mean absolute position errors and yaw deviations constrained within 5.688 degrees. These results confirm the effectiveness of the proposed lateral force generation model and provide a foundation for the development of agile, hover-capable tail-sitter UAVs.

The growing integration of drones across commercial, industrial, and civilian domains has introduced significant cybersecurity challenges, particularly due to the susceptibility of drone networks to a wide range of cyberattacks. Existing intrusion detection mechanisms often lack the adaptability, efficiency, and generalizability required for the dynamic and resource constrained environments in which drones operate. This paper proposes TSLT-Net, a novel lightweight and unified Temporal Spatial Transformer based intrusion detection system tailored specifically for drone networks. By leveraging self attention mechanisms, TSLT-Net effectively models both temporal patterns and spatial dependencies in network traffic, enabling accurate detection of diverse intrusion types. The framework includes a streamlined preprocessing pipeline and supports both multiclass attack classification and binary anomaly detection within a single architecture. Extensive experiments conducted on the ISOT Drone Anomaly Detection Dataset, consisting of more than 2.3 million labeled records, demonstrate the superior performance of TSLT-Net with 99.99 percent accuracy in multiclass detection and 100 percent in binary anomaly detection, while maintaining a minimal memory footprint of only 0.04 MB and 9722 trainable parameters. These results establish TSLT-Net as an effective and scalable solution for real time drone cybersecurity, particularly suitable for deployment on edge devices in mission critical UAV systems.

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? Five people have been killed in Ukraine after Russia launched hundreds of drones and missiles across the country overnight, which officials said targeted civilian infrastructure. Ukraine's President Volodymyr Zelenskyy said on Sunday that Russia fired approximately 50 missiles and 500 attack drones.