Zelensky said Russian strikes also targeted Kharkiv and Sumy, and added on X that the strikes "cannot be left without response, and Ukrainian long-range drones ensure one". He added that Russian military sites and airports "must see that Russia's own war is now hitting them back with real consequences" and said Ukraine's drone attacks were "some of the arguments that will surely bring peace closer". Six people were injured in the strikes on Dnipropetrovsk, the region's head said. A residential block and industrial areas were hit in the city of Dnipro while a shopping centre was hit in the wider district. Also on Saturday, Russia's ministry of defence claimed its army had captured two villages, Zelenyi Hai in the Donetsk region and Maliivka in the Dnipropetrovsk region.

A solar-powered surveillance drone with a wingspan larger than a Boeing 747 jumbo jet could fly for weeks or months at a time, according to its operator, while watching for drug-smuggling vessels, pirates or naval warships. It has been performing test flights off the US Gulf Coast this month. The Skydweller drone, operated by US-Spanish firm Skydweller Aero, has a wingspan of 72 metres – exceeding the width of most commercial passenger jets. But it weighs only about 2500 kilograms – as much as a Ford F-150 truck. It is based on the Solar Impulse 2 aircraft, which performed the first solar-powered flight around the world in 2016. Skydweller Aero purchased and converted the pioneering aircraft with the goal of building a fleet of similar solar-powered, carbon-fibre drones capable of "perpetual flight" at altitudes exceeding 13 kilometres in daytime hours.

In this paper, we present a subsystem, using Unmanned Aerial Vehicles (UAV), for search and rescue missions, focusing on people detection, face recognition and tracking of identified individuals. The proposed solution integrates a UAV with ROS2 framework, that utilizes multiple convolutional neural networks (CNN) for search missions. System identification and PD controller deployment are performed for autonomous UAV navigation. The ROS2 environment utilizes the YOLOv11 and YOLOv11-pose CNNs for tracking purposes, and the dlib library CNN for face recognition. The system detects a specific individual, performs face recognition and starts tracking. If the individual is not yet known, the UAV operator can manually locate the person, save their facial image and immediately initiate the tracking process. The tracking process relies on specific keypoints identified on the human body using the YOLOv11-pose CNN model. These keypoints are used to track a specific individual and maintain a safe distance. To enhance accurate tracking, system identification is performed, based on measurement data from the UAVs IMU. The identified system parameters are used to design PD controllers that utilize YOLOv11-pose to estimate the distance between the UAVs camera and the identified individual. The initial experiments, conducted on 14 known individuals, demonstrated that the proposed subsystem can be successfully used in real time. The next step involves implementing the system on a large experimental UAV for field use and integrating autonomous navigation with GPS-guided control for rescue operations planning.

-- Multi-UA V Coverage Path Planning (mCPP) algorithms in popular commercial software typically treat a Region of Interest (RoI) only as a 2D plane, ignoring important 3D structure characteristics. This leads to incomplete 3D reconstructions, especially around occluded or vertical surfaces. In this paper, we propose a modular algorithm that can extend commercial two-dimensional path planners to facilitate terrain-aware planning by adjusting altitude and camera orientations. T o demonstrate it, we extend the well-known DARP (Divide Areas for Optimal Multi-Robot Coverage Path Planning) algorithm and produce DARP-3D. Compared to baseline, our approach consistently captures improved 3D reconstructions, particularly in areas with significant vertical features. An open-source implementation of the algorithm is available here: https://github.com/konskara/T

Path smoothness is often overlooked in path imitation learning from expert demonstrations. In this paper, we introduce a novel learning method, termed deep angular A* (DAA*), by incorporating the proposed path angular freedom (PAF) into A* to improve path similarity through adaptive path smoothness. The PAF aims to explore the effect of move angles on path node expansion by finding the trade-off between their minimum and maximum values, allowing for high adaptiveness for imitation learning. DAA* improves path optimality by closely aligning with the reference path through joint optimization of path shortening and smoothing, which correspond to heuristic distance and PAF, respectively. Throughout comprehensive evaluations on 7 datasets, including 4 maze datasets, 2 video-game datasets, and a real-world drone-view dataset containing 2 scenarios, we demonstrate remarkable improvements of our DAA* over neural A* in path similarity between the predicted and reference paths with a shorter path length when the shortest path is plausible, improving by 9.0% SPR, 6.9% ASIM, and 3.9% PSIM. Furthermore, when jointly learning pathfinding with both path loss and path probability map loss, DAA* significantly outperforms the state-of-the-art TransPath by 6.3% SPR, 6.0% PSIM, and 3.7% ASIM. We also discuss the minor trade-off between path optimality and search efficiency where applicable. Our code and model weights are available at https://github.com/zwxu064/DAAStar.git.

Retired Air Force Gen. Charles Wald joins'Fox News Live' to weigh in on Russia's increased attacks on Ukraine despite President Donald Trump's ultimatum to Vladimir Putin. Russia and Ukraine took aim at corresponding Black Sea resort cities early Thursday morning, just hours after ceasefire talks in Turkey once again failed to deliver results. The major Russian resort city of Sochi was rocked by a Ukrainian drone strike that began around 1 a.m. and lasted until 3 a.m., where one person was reportedly killed and another injured, according to Ukrainian media outlet the Kyiv Independent, though the Ukrainian military has not commented on the incident. An oil depot in the Krasnodar Krai region where Sochi is located was also struck, though the extent of the damage remains unclear. Russia's President Vladimir Putin chairs a meeting via a video conference at the Kremlin in Moscow on July 23, 2025.

But Peskov poured cold water on the idea, saying it was "premature" for the two presidents to meet. "They [Ukraine] are trying to put the cart slightly ahead of the horse," he said, adding much more work had to be done before any such meeting could take place. Ukrainian MP Oleksiy Hocharenko said on Facebook that a separate meeting between Umerov and Medinsky had taken place behind closed doors on the sidelines of the main talks. Hocharenko said Umerov and Medinsky have a "good relationship". The first two rounds of ceasefire talks were held in May and June at the request of US President Donald Trump, who has repeatedly said he wants to see the end of the "horrible, bloody war" that was sparked by Russia's invasion of Ukraine in 2022.

An NYPD drone observed four minors, between the ages of 12 and 16 years old, riding on top of a train in the Bronx on Thursday as it passed multiple stations at a high speed. FIRST ON FOX: A new move by Congress would unleash civilian drone use across America's skies by establishing rules to allow them to be flown beyond a user's line of sight and using AI for approval to do so. Her LIFT Act, introduced in the House on Thursday, would require Transportation Secretary Sean Duffy to establish set performance and safety standards for BVLOS operations and review current aviation standards, which were designed with manned aircraft in mind. It would also require the Transportation secretary to deploy artificial intelligence to assist with processing waiver applications to allow civilian drones to fly BVLOS. Industry operators have long pushed for new BVLOS policy to replace the current system in which individuals must apply for waivers with the Federal Aviation Adminsitration (FAA) through a costly, cumbersome process to fly beyond the line of sight.

Chinese-made engines are being covertly shipped via front companies to a state-owned drone manufacturer in Russia, labeled as "industrial refrigeration units" to avoid detection in the wake of Western sanctions, according to three European security officials and documents. The shipments have allowed Russian weapons-maker IEMZ Kupol to increase its production of the Garpiya-A1 attack drone, despite the U.S. and EU sanctions imposed in October designed to disrupt its supply chain, according to the sources and documents, which included contracts, invoices and customs paperwork. An internal Kupol document showed it signed a contract with the Russian defense ministry to produce more than 6,000 Garpiya this year, up from 2,000 in 2024. The document stated that more than 1,500 drones had already been delivered by April.

Autonomous drones have gained considerable attention for applications in real-world scenarios, such as search and rescue, inspection, and delivery. As their use becomes ever more pervasive in civilian applications, failure to ensure safe operation can lead to physical damage to the system, environmental pollution, and even loss of human life. Recent work has demonstrated that motion planning techniques effectively generate a collision-free trajectory during navigation. However, these methods, while creating the motion plans, do not inherently consider the safe operational region of the system, leading to potential safety constraints violation during deployment. In this paper, we propose a method that leverages run time safety assurance in a kinodynamic motion planning scheme to satisfy the system's operational constraints. First, we use a sampling-based geometric planner to determine a high-level collision-free path within a user-defined space. Second, we design a low-level safety assurance filter to provide safety guarantees to the control input of a Linear Quadratic Regulator (LQR) designed with the purpose of trajectory tracking. We demonstrate our proposed approach in a restricted 3D simulation environment using a model of the Crazyflie 2.0 drone.