French troops board oil tanker linked to Russian'shadow fleet' French soldiers have boarded an oil tanker believed to be part of Russia's shadow fleet, used to evade sanctions imposed because of the war in Ukraine. The Boracay left Russia last month and was off the coast of Denmark when unidentified drones forced the temporary closure of several airports last week. It has been anchored off western France for a few days. French President Emmanuel Macron said at an EU leaders' summit in Copenhagen on Wednesday that the crew had committed serious offences, but did not elaborate. Kremlin spokesman Dmitry Peskov said Russia had no knowledge of the vessel.

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? Macron, Meloni argue for caution in responding to Russian'provocations' Danish Prime Minister Mette Frederiksen has called on Europe to arm itself to respond to Russia's hybrid warfare, but other major continental leaders have argued for caution against getting trapped in a tit-for-tat cycle of escalation with Moscow. "I hope that everybody recognises now that there is a hybrid war and one day it's Poland, the other day it's Denmark, and next week it will probably be somewhere else that we see sabotage or we see drones flying," Frederiksen told reporters on Wednesday.

Flytrex and Uber Eats will begin testing drone food delivery in select U.S. markets by year-end, potentially reducing delivery times to just minutes for customers.

Accurate visual localization from aerial views is a fundamental problem with applications in mapping, large-area inspection, and search-and-rescue operations. In many scenarios, these systems require high-precision localization while operating with limited resources (e.g., no internet connection or GNSS/GPS support), making large image databases or heavy 3D models impractical. Surprisingly, little attention has been given to leveraging orthographic geodata as an alternative paradigm, which is lightweight and increasingly available through free releases by governmental authorities (e.g., the European Union). To fill this gap, we propose OrthoLoC, the first large-scale dataset comprising 16,425 UAV images from Germany and the United States with multiple modalities. The dataset addresses domain shifts between UAV imagery and geospatial data. Its paired structure enables fair benchmarking of existing solutions by decoupling image retrieval from feature matching, allowing isolated evaluation of localization and calibration performance. Through comprehensive evaluation, we examine the impact of domain shifts, data resolutions, and covisibility on localization accuracy. Finally, we introduce a refinement technique called AdHoP, which can be integrated with any feature matcher, improving matching by up to 95% and reducing translation error by up to 63%. The dataset and code are available at: https://deepscenario.github.io/OrthoLoC.

A core challenge in AI-guided autonomy is enabling agents to navigate realistically and effectively in previously unseen environments based on natural language commands. We propose UAV-VLN, a novel end-to-end Vision-Language Navigation (VLN) framework for Unmanned Aerial Vehicles (UAVs) that seamlessly integrates Large Language Models (LLMs) with visual perception to facilitate human-interactive navigation. Our system interprets free-form natural language instructions, grounds them into visual observations, and plans feasible aerial trajectories in diverse environments. UAV-VLN leverages the common-sense reasoning capabilities of LLMs to parse high-level semantic goals, while a vision model detects and localizes semantically relevant objects in the environment. By fusing these modalities, the UAV can reason about spatial relationships, disambiguate references in human instructions, and plan context-aware behaviors with minimal task-specific supervision. To ensure robust and interpretable decision-making, the framework includes a cross-modal grounding mechanism that aligns linguistic intent with visual context. We evaluate UAV-VLN across diverse indoor and outdoor navigation scenarios, demonstrating its ability to generalize to novel instructions and environments with minimal task-specific training. Our results show significant improvements in instruction-following accuracy and trajectory efficiency, highlighting the potential of LLM-driven vision-language interfaces for safe, intuitive, and generalizable UAV autonomy.

Why is Denmark being targeted with mystery drone flights? Police officers stand guard after all traffic has been closed at Copenhagen Airport due to drone reports on Sept. 22 | Ritzau Scanpix / via REUTERS Copenhagen - Denmark's support for Ukraine, its lack of anti-drone defenses and this week's EU summit in Copenhagen could all explain the unidentified drone sightings over Danish airspace that have been widely blamed on Russia. Drones have been seen across the Scandinavian country, including over military sites, since Sept. 22, prompting brief closures at several airports and a ban on all civilian drone flights until Friday. The drone intrusions were extremely well-executed and also clearly designed to humiliate the authorities, just to show that you can actually fly drones over Danish airports and critical infrastructure, said Rasmus Dahlberg, an expert on hybrid threats. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Danish PM calls for strong answer from EU leaders to Russia's hybrid attacks EU leaders have met in Copenhagen under pressure to boost European defence after a series of Russian incursions into EU airspace, and days after drones targeted Danish airports. Danish Prime Minister Mette Frederiksen told reporters that from a European perspective there is only one country... willing to threaten us and that is Russia, and therefore we need a very strong answer back. The incursions have become most acute for countries on the EU's eastern flank such as Poland and Estonia. A number of member states have already backed plans for a multi-layered drone wall to quickly detect, then track and destroy Russian drones. We meet at a time when Russia have intensified their attacks in Ukraine, where we have seen Russian airspace violations and unwanted drone activity in several European countries, Frederiksen told a news conference after the talks had concluded.

The hype around delivery robots has fizzled, but DoorDash is still determined to launch Dot, an adorable red bot. It can ride on roads and in bike lanes, where it will face daunting challenges. DoorDash's new delivery robot is named Dot. When we first got close to Dot, DoorDash's new delivery robot, we looked right into its big blue, pixelated eyes and gave it a kick. It's not WIRED's policy to be mean to 350-pound hunks of plastic on wheels.

An entire family - a married couple and their two young sons - have been killed in an overnight Russian drone attack in Ukraine's north-eastern Sumy region, local officials have said. Regional head Oleh Hryhorov said a residential building was hit in the village of Chernechchyna. The bodies of the two children, aged four and six, and their parents were later recovered from the wreckage. Ukraine's air force said its units shot down 46 out of 65 Russian drones across the country - but there were 19 direct hits in six locations. Russia's military has not commented.

The FAA is set to loosen rules to let people fly drones beyond their "line of sight. On Thursday, I published a story about the police-tech giant Flock Safety selling its drones to the private sector to track shoplifters. Keith Kauffman, a former police chief who now leads Flock's drone efforts, described the ideal scenario: A security team at a Home Depot, say, launches a drone from the roof that follows shoplifting suspects to their car. The drone tracks their car through the streets, transmitting its live video feed directly to the police. It's a vision that, unsurprisingly, alarms civil liberties advocates. They say it will expand the surveillance state created by police drones, license-plate readers, and other crime tech, which has allowed law enforcement to collect massive amounts of private data without warrants.