Russia unleashed an overnight drone attack across Ukraine targeting the capital Kyiv and hitting infrastructure in the Black Sea port of Odesa, Ukrainian officials said. The State Emergency Service said one person was injured and warehouses and cargo trucks damaged in Odesa during the multi-wave attack, which kept much of the country under air-raid alert for several hours. The Ukrainian Air Force said the Russian attack involved 87 attack drones and four missiles. Air defence units destroyed 56 of the drones and two of the missiles, the Air Force said. Anti-Kremlin activist Ildar Dadin, who was jailed in Russia for protesting against President Vladimir Putin, was killed on the front line in Ukraine where he was fighting alongside Kyiv's forces, his relatives and Russian media said.

This manuscript details an architecture and training methodology for a data-driven framework aimed at detecting, identifying, and quantifying damage in the propeller blades of multirotor Unmanned Aerial Vehicles. By substituting one propeller with a damaged counterpart-encompassing three distinct damage types of varying severity-real flight data was collected. This data was then used to train a composite model, comprising both classifiers and neural networks, capable of accurately identifying the type of failure, estimating damage severity, and pinpointing the affected rotor. The data employed for this analysis was exclusively sourced from inertial measurements and control command inputs, ensuring adaptability across diverse multirotor vehicle platforms.

A novel approach for robust state estimation of marine vessels in rough water is proposed in this paper to enable tight collaboration between Unmanned Aerial Vehicles (UAVs) and a marine vessel, such as cooperative landing or object manipulation, regardless of weather conditions. Our study of marine vessel (in our case Unmanned Surface Vehicle (USV)) dynamics influenced by strong wave motion has resulted in a novel nonlinear mathematical USV model with 6 degrees of freedom (DOFs), which is required for precise USV state estimation and motion prediction. The proposed state estimation approach fuses data from multiple sensors onboard the UAV and the USV to enable redundancy and robustness under varying weather conditions of real-world applications. The proposed approach provides estimated states of the USV with 6 DOFs and predicts its future states to enable tight control of both vehicles on a receding control horizon. The proposed approach was extensively tested in the realistic Gazebo simulator and successfully experimentally validated in many real-world experiments representing different application scenarios, including agile landing on an oscillating and moving USV. A comparative study indicates that the proposed approach significantly surpassed the current state-of-the-art.

Precision livestock farming (PLF) aims to improve the health and welfare of livestock animals and farming outcomes through the use of advanced technologies. Computer vision, combined with recent advances in machine learning and deep learning artificial intelligence approaches, offers a possible solution to the PLF ideal of 24/7 livestock monitoring that helps facilitate early detection of animal health and welfare issues. However, a significant number of livestock species are raised in large outdoor habitats that pose technological challenges for computer vision approaches. This review provides a comprehensive overview of computer vision methods and open challenges in outdoor animal monitoring. We include research from both the livestock and wildlife fields in the review because of the similarities in appearance, behaviour, and habitat for many livestock and wildlife. We focus on large terrestrial mammals, such as cattle, horses, deer, goats, sheep, koalas, giraffes, and elephants. We use an image processing pipeline to frame our discussion and highlight the current capabilities and open technical challenges at each stage of the pipeline. The review found a clear trend towards the use of deep learning approaches for animal detection, counting, and multi-species classification. We discuss in detail the applicability of current vision-based methods to PLF contexts and promising directions for future research.

Reach-Avoid-Stay (RAS) optimal control enables systems such as robots and air taxis to reach their targets, avoid obstacles, and stay near the target. However, current methods for RAS often struggle with handling complex, dynamic environments and scaling to high-dimensional systems. While reinforcement learning (RL)-based reachability analysis addresses these challenges, it has yet to tackle the RAS problem. In this paper, we propose a two-step deep deterministic policy gradient (DDPG) method to extend RL-based reachability method to solve RAS problems. First, we train a function that characterizes the maximal robust control invariant set within the target set, where the system can safely stay, along with its corresponding policy. Second, we train a function that defines the set of states capable of safely reaching the robust control invariant set, along with its corresponding policy. We prove that this method results in the maximal robust RAS set in the absence of training errors and demonstrate that it enables RAS in complex environments, scales to high-dimensional systems, and achieves higher success rates for the RAS task compared to previous methods, validated through one simulation and two high-dimensional experiments.

Forget adulting for a minute. What does your inner child want today? We're betting it's something fun that takes you back to your childhood, where you can explore the great outdoors and just feel like a kid again. How about one of those drones you keep seeing on Instagram and Facebook? They aren't as expensive as you might think.

The Kremlin on Friday accused Ukrainian authorities of playing with fire, a day after Russian forces said they had intercepted a Ukrainian drone near the Kursk nuclear plant and some news outlets reported a fire had broken out several miles away. Ukrainian Ministry of Foreign Affairs spokesman Heorhiy Tykhyi denied that his country had fired weapons at or near the plant.

The United States military has struck a number of cities in Yemen, including the capital, Sanaa, and the key port city of Hodeidah. Forces from the US Central Command (CENTCOM), the military command responsible for US forces in the Middle East, "conducted strikes on 15 Houthi targets in Iranian-backed Houthi-controlled areas of Yemen today", it said on X on Friday. Four strikes targeted Sanaa and seven hit Hodeidah, according to the Houthi-run Al Masirah TV network. Correspondents with the AFP news agency also reported hearing loud explosions in both cities. The Hodeidah strikes hit the airport and the Katheib area, which has a Houthi-controlled military base, Al Masirah said.

Gen. Jack Keane joins'Fox Report' to discuss the escalating tensions in the Middle East amid fears of a wider war. While much of the world has eyes on Israel's battles with Hezbollah and Hamas, the U.S. Navy has its sights set on another of Iran's proxies, the Yemeni Houthi rebels. With a mission to keep international waterways at peace, the Navy now finds itself fending off attacks from the shadowy gang of pirates who have gone from arming themselves with assault rifles, pickup trucks and motorboats – to a seemingly unending supply of drones, missiles and other weaponry. The Houthis often attack unarmed Western ships carrying goods through the Red Sea and the Gulf of Aden – while the U.S. has responded in kind with drone attacks on Yemen. ISRAELI AIR FORCE STRIKES HOUTHI TARGETS IN YEMEN WITH'EXTENSIVE' OPERATION That's led to perilous waters along a trade route that typically sees some 1 trillion in goods pass through it, as well as shipments of aid to war-torn Sudan and the Yemeni people.

At least three people, including a six-year-old girl, were killed after Russian drones hit a truck delivering gas cylinders to houses in a border village in the northern Chernihiv region, Ukraine's national police force said on Telegram. Four people, including two children, were injured. At least 12 people, including a three-year-old girl, were injured after a Russian glide bomb struck a five-storey apartment block in northeastern Kharkiv, Ukraine's second-largest city. The bomb struck late on Wednesday night, starting a fire, the regional governor said. Russia's Ministry of Defence said its army had taken full control of the strategic hilltop town of Vuhledar in eastern Ukraine.