Drones have been seen near military facilities including Denmark's largest, following a series of incidents that caused air disruption earlier this week. The devices were observed above Karup airbase, among others, forcing it to briefly close its airspace to commercial traffic. Possible sightings were also reported in Germany, Norway and Lithuania. It is the latest in a string of suspicious drone activity in Denmark, raising concerns about the nation's vulnerability to aerial attack and sparking fears of potential Russian involvement. Danish authorities said Thursday's incursions appeared to be a hybrid attack, but cautioned that they had no evidence to suggest Moscow was behind it.

Drone footage has captured a group of polar bears living inside an abandoned research station on Russia's Kolyuchin Island. Travel blogger, Vadim Makhorov, shared video that shows several bears inside the scattered building, looking through windows and walking around the island. A bear could be seen trying to catch the blogger's drone as it approached. The Kolyuchin weather station was abandoned in the early 1990s, after the collapse of the Soviet Union. Russian Alexey Molchanov breaks his own 2024 world record in one of the most technically challenging freediving events.

Russian freediver Alexey Molchanov plunged 126m (413ft) in a single breath to set a new world record at the AIDA Freediving World Championships in Limassol, Cyprus. He descended deep below the Mediterranean Sea with nothing but a headlight, two fins and a rope as a guide, in a feat considered one of the most technically challenging freedive categories. Mr Molchanov broke his own 2024 world record of 125m, during which he held his breath for a staggering four minutes and 32 seconds. The BBC's Russia editor, Steve Rosenberg, reports from joint manoeuvres by Russia and Belarus, as part of the Zapad 2025 (West 2025) military drills. 'Looks like a toy, but it's real': BBC examines a downed Russian drone Drones like this one were shot down over Polish airspace in the early hours of Wednesday.

Drone maker DJI loses lawsuit to exit Pentagon's list of firms with Chinese military ties A U.S. judge on Friday rejected a bid by China-based DJI, the world's largest drone maker, to be removed from the U.S. Defense Department's list of companies allegedly working with Beijing's military. In his ruling, U.S. District Judge Paul Friedman in Washington, D.C., said the Defense Department had substantial evidence supporting its finding that DJI, which sells more than half of all U.S. commercial drones, contributes to the Chinese defense industrial base." DJI had urged the court to order its removal from the Pentagon list designating it as a Chinese military company, saying it is neither owned nor controlled by the Chinese military. The judge rejected some of the government's other justifications for listing DJI. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

We study last-mile delivery with one truck and one drone under explicit battery management: the drone flies at twice the truck speed; each sortie must satisfy an endurance budget; after every delivery the drone recharges on the truck before the next launch. We introduce a hybrid reinforcement learning (RL) solver that couples an ALNS-based truck tour (with 2/3-opt and Or-opt) with a small pointer/attention policy that schedules drone sorties. The policy decodes launch-serve-rendezvous triplets with hard feasibility masks for endurance and post-delivery recharge; a fast, exact timeline simulator enforces launch/recovery handling and computes the true makespan used by masked greedy/beam decoding. On Euclidean instances with $N{=}50$, $E{=}0.7$, and $R{=}0.1$, the method achieves an average makespan of \textbf{5.203}$\pm$0.093, versus \textbf{5.349}$\pm$0.038 for ALNS and \textbf{5.208}$\pm$0.124 for NN -- i.e., \textbf{2.73\%} better than ALNS on average and within \textbf{0.10\%} of NN. Per-seed, the RL scheduler never underperforms ALNS on the same instance and ties or beats NN on two of three seeds. A decomposition of the makespan shows the expected truck-wait trade-off across heuristics; the learned scheduler balances both to minimize the total completion time. We provide a config-first implementation with plotting and significance-test utilities to support replication.

Can Ukraine restore its pre-war borders? Is Russia testing NATO with aerial incursions in Europe? EU to develop'drone wall' amid regional airspace violations European Union defence ministers have agreed to develop a "drone wall" along their borders with Russia and Ukraine to detect, track and intercept violations of their airspace, according to the bloc's defence chief. Friday's announcement comes after rogue drones entered Polish airspace on September 10, rattling eastern EU members. Although Danish authorities have not concluded their investigations, Frederiksen stressed that Russia was currently the primary threat to European security. The Kremlin has denied any involvement in the drone incidents in Poland and Denmark.

After significantly weakening other Iranian-backed groups in the region, Israel's military has turned its attention to the Houthis, carrying out a series of punishing strikes on Yemeni ports and other infrastructure. Last month an Israeli attack in Sana killed senior members of the Houthi-led government -- including the prime minister, Ahmed al-Rahawi -- but appeared to leave the group's military leadership largely unscathed. Israeli strikes in Yemen have also killed and wounded dozens of civilians in recent months, according to human rights groups. The United States has also bombed Yemen, in response to Houthi attacks on Red Sea shipping. The Houthis say they have targeted ships linked to Israel, although some of the ships they struck have no clear connection to the country. Houthi attacks on Israel are typically blocked or intercepted by the Israeli military, as was the case late on Thursday when sirens sounded in parts of Israel and the military soon after said that a missile from Yemen had been thwarted.

Chinese drone experts have flown to Russia to conduct technical development work on military drones at a state-owned weapons manufacturer that is under Western sanctions, according to two European security officials and documents. The Chinese experts have visited arms maker IEMZ Kupol on more than half a dozen occasions since the second quarter of last year. During that time, Kupol also received shipments of Chinese-made attack and surveillance drones via a Russian intermediary, according to the documents and two officials. In September last year, it was documented that Kupol had developed a new drone, the Garpiya-3, in China with the help of local specialists, with specific details of the extensive involvement of Chinese experts in tests and technological work on military-use drones inside Russia now being reported for the first time. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Abstract-- 3D object localisation based on a sequence of camera measurements is essential for safety-critical surveillance tasks, such as drone-based wildfire monitoring. Localisation of objects detected with a camera can typically be solved with dense depth estimation or 3D scene reconstruction. However, in the context of distant objects or tasks limited by the amount of available computational resources, neither solution is feasible. In this paper, we show that the task can be solved using particle filters for both single and multiple target scenarios. The method was studied using a 3D simulation and a drone-based image segmentation sequence with global navigation satellite system (GNSS)-based camera pose estimates. The results showed that a particle filter can be used to solve practical localisation tasks based on camera poses and image segments in these situations where other solutions fail. The particle filter is independent of the detection method, making it flexible for new tasks. The study also demonstrates that drone-based wildfire monitoring can be conducted using the proposed method paired with a pre-existing image segmentation model.

Autonomous exploration in structured and complex indoor environments remains a challenging task, as existing methods often struggle to appropriately model unobserved space and plan globally efficient paths. To address these limitations, we propose GUIDE, a novel exploration framework that synergistically combines global graph inference with diffusion-based decision-making. We introduce a region-evaluation global graph representation that integrates both observed environmental data and predictions of unexplored areas, enhanced by a region-level evaluation mechanism to prioritize reliable structural inferences while discounting uncertain predictions. Building upon this enriched representation, a diffusion policy network generates stable, foresighted action sequences with significantly reduced denoising steps. Extensive simulations and real-world deployments demonstrate that GUIDE consistently outperforms state-of-the-art methods, achieving up to 18.3% faster coverage completion and a 34.9% reduction in redundant movements.