Russian drone strikes have killed three people and wounded 60, including children, in the northeastern city of Kharkiv, officials say. The city, just 30 kilometres (18 miles) from the Russian border, bore the brunt of Russia's latest aerial assault early on Wednesday, with 17 drones striking two residential areas, Mayor Ihor Terekhov said. "Those are ordinary sites of peaceful life … that should never be targeted," he wrote on Telegram. Among the 60 wounded in the attacks were nine children aged between 2 and 15, according to Kharkiv regional head Oleh Syniehubov. One Kharkiv resident, Olena Khoruzheva, told the AFP news agency how she had run with her two children away from the windows of her building when she heard the drones approach.

During an address at Fort Bragg on Tuesday, President Trump announced that several Army base titles would be restored to their original names after changes made during the Biden administration. The U.S. Army is giving its soldiers a high-tech edge in the fight against drones, and it's called SMASH. During a live-fire training exercise on June 6 in Germany, a soldier with the 3rd Squadron, 2nd Cavalry Regiment used the SMASH 2000L smart scope mounted on an M4A1 rifle to target drones in the sky. The demo was part of Project Flytrap, a multinational training event. U.S. Soldiers assigned to 3rd Squadron, 2nd Cavalry Regiment set up the Wingman and Pitbull portable counter-unmanned aerial system devices during Project Flytrap at Joint Multinational Readiness Center, Hohenfels Training Area, Hohenfels, Germany, June 7, 2025.

Russia launched a large-scale drone-and-missile assault on Ukraine, killing one person in Kyiv and two in the southern port city of Odesa. At least 13 people were injured. A Ukrainian drone attack on a petrol station in the Russian city of Belgorod killed one person and injured four others, the region's governor, Vyacheslav Gladkov, said. Ukrainian President Volodymyr Zelenskyy said Russia's attack on Kyiv was "one of the biggest" in the three-year-old war. It caused several fires and damaged buildings, including St Sophia Cathedral, a UNESCO World Heritage landmark.

MOMAV (Marco's Omnidirectional Micro Aerial Vehicle) is a multirotor drone that is fully actuated, meaning it can control its orientation independently of its position. MOMAV is also highly symmetrical, making its flight efficiency largely unaffected by its current orientation. These characteristics are achieved by a novel drone design where six rotor arms align with the vertices of an octahedron, and where each arm can actively rotate along its long axis. Various standout features of MOMAV are presented: The high flight efficiency compared to arm configuration of other fully-actuated drones, the design of an original rotating arm assembly featuring slip-rings used to enable continuous arm rotation, and a novel control allocation algorithm based on sequential quadratic programming (SQP) used to calculate throttle and arm-angle setpoints in flight. Flight tests have shown that MOMAV is able to achieve remarkably low mean position/orientation errors of 6.6mm, 2.1° (σ: 3.0mm, 1.0°) when sweeping position setpoints, and 11.8mm, 3.3° (σ: 8.6mm, 2.0°) when sweeping orientation setpoints.

Agentic UAVs represent a new frontier in autonomous aerial intelligence, integrating perception, decision-making, memory, and collaborative planning to operate adaptively in complex, real-world environments. Driven by recent advances in Agentic AI, these systems surpass traditional UAVs by exhibiting goal-driven behavior, contextual reasoning, and interactive autonomy. We provide a comprehensive foundation for understanding the architectural components and enabling technologies that distinguish Agentic UAVs from traditional autonomous UAVs. Furthermore, a detailed comparative analysis highlights advancements in autonomy with AI agents, learning, and mission flexibility. This study explores seven high-impact application domains precision agriculture, construction & mining, disaster response, environmental monitoring, infrastructure inspection, logistics, security, and wildlife conservation, illustrating the broad societal value of agentic aerial intelligence. Furthermore, we identify key challenges in technical constraints, regulatory limitations, and data-model reliability, and we present emerging solutions across hardware innovation, learning architectures, and human-AI interaction. Finally, a future roadmap is proposed, outlining pathways toward self-evolving aerial ecosystems, system-level collaboration, and sustainable, equitable deployments. This survey establishes a foundational framework for the future development, deployment, and governance of agentic aerial systems (Agentic UAVs) across diverse societal and industrial domains.

This paper presents an adaptive path planner for object search in agricultural fields using UAVs. The path planner uses a high-altitude coverage flight path and plans additional low-altitude inspections when the detection network is uncertain. The path planner was evaluated in an offline simulation environment containing real-world images. We trained a YOLOv8 detection network to detect artificial plants placed in grass fields to showcase the potential of our path planner. We evaluated the effect of different detection certainty measures, optimized the path planning parameters, investigated the effects of localization errors, and different numbers of objects in the field. The YOLOv8 detection confidence worked best to differentiate between true and false positive detections and was therefore used in the adaptive planner. The optimal parameters of the path planner depended on the distribution of objects in the field. When the objects were uniformly distributed, more low-altitude inspections were needed compared to a non-uniform distribution of objects, resulting in a longer path length. The adaptive planner proved to be robust against localization uncertainty. When increasing the number of objects, the flight path length increased, especially when the objects were uniformly distributed. When the objects were non-uniformly distributed, the adaptive path planner yielded a shorter path than a low-altitude coverage path, even with a high number of objects. Overall, the presented adaptive path planner allowed finding non-uniformly distributed objects in a field faster than a coverage path planner and resulted in a compatible detection accuracy. The path planner is made available at https://github.com/wur-abe/uav_adaptive_planner.

Russia and Ukraine are waging a remotely controlled battle in the air and at sea that the world's militaries are closely watching for insights.

In the three months before August last year, Russia fired a total of 1,100, according to a report by Ukraine's general staff. A steep rise followed, with 818 drones recorded in August, 1,410 in September and more than 2,000 in October. But the numbers just keep going up. In May, for the first time, the number of drones exceeded 4,000. This month is likely to set a new record.

Russia launched a major drone attack on Ukraine overnight, damaging buildings in Kyiv and hitting a maternity ward in Odesa. Two people were killed and several others injured. Ukrainian President Volodymyr Zelenskyy described the attack as "one of the biggest" of the war, saying Moscow's forces fired more than 315 drones and seven missiles.

Russia launched large drone attacks on Kyiv and the southern port of Odesa on Tuesday morning, regional authorities said. Timur Tkachenko, the head of Kyiv's military administration, said that several districts of the capital were being attacked simultaneously, resulting in damage to buildings and fires. Oleh Kiper, the governor of the Odesa region, said on Telegram that a "massive" drone attack struck an emergency medical building, a maternity ward and residential buildings. Kiper said that a 59-year-old man was killed and four others injured in the attack on residential buildings, but there were no casualties at the maternity ward. Russian air defence systems destroyed 76 Ukrainian drones over a two-hour period on Monday, Russian media outlets reported.