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People walk past a sign reading No drone zone in an alley in Beijing on Sept. 14. | AFP-JIJI Beijing - Drone owners in Beijing flocked to designated buy-back sites in recent days, looking to sell their devices for as much as possible ahead of an impending citywide ban. New rules in the Chinese capital ban not just the flying of unmanned aerial vehicles but the possession or storage of them, meaning owners have until November 15 to get rid of their drones. At several authorized buyer sites across the city, reporters witnessed queues of people waiting for staff to appraise their drones and negotiate prices. All sites had a visible police presence, indicating the sensitivity of the new laws, and most people there did not want to talk to reporters. At the flagship store for the world's largest drone-maker DJI in Beijing's business district, around a dozen people queued on Thursday morning hoping to sell their drones back for a reasonable price.

The retrofitted Cessna handled taxiing, takeoffs, bad weather, and landings without a human pilot. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. A human safety pilot flew onboard during the trip, but never needed to assist the flight. A single-engine prop Cessna Caravan has reportedly become the first airplane to autonomously complete a cross-continental flight across the United States. Overseen by the aeronautics company Joby, the retrofitted aircraft began its challenge in Concord, California, on September 7, ultimately traveling 3,199 miles with no assistance from its onboard human safety pilot.

Will self-flying planes transform the skies? Image caption, Pyka's crop dusters are used in the US and Brazil Over an alfalfa field in California's San Joaquin Valley, a small crop-spraying plane is flying scarily low to the ground. There's little risk to humans though, as the plane is pilot-free. We can actually go lower than a human pilot can, says Russ Marotzke, as the aircraft skims over the crop. Flying lower means less spray drift and therefore less chemicals are needed than in conventional manned crop-dusting, he says.

Technology Aviation The world's largest electric plane takes flight The 25,000-pound aircraft flew for 27 minutes. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Heart Aerospace's X1 demonstrator, the largest battery-electric aircraft ever flown, crosses the Champlain Valley near Plattsburgh, New York, at sunrise during its first flight in August 2026. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

Security researchers found that in less than 60 seconds, they could open a hatch on a plane's exterior, plug in a tiny device, and redirect the aircraft's autopilot or sabotage its flight plan. Even as the digital components of so many life-critical systems have proven susceptible to cybersabotage-- cars, medical devices, even water utilities and power grids --the computer systems of airplanes have, thankfully, remained uniquely inaccessible to hackers. But one group of academic researchers has spent years testing a different, devious approach to aviation cybersecurity. Perhaps, they suggest, a plane could be hacked the same way that spies and saboteurs have targeted other high-value, offline computers: by surreptitiously gaining physical access to one and plugging in a device designed to silently run the attackers' malicious code. Tomorrow at the Usenix Cybersecurity Conference, researchers from the University of California at San Diego and Oberlin College will present a hacking technique capable of commandeering the autopilot of a Boeing 737 to redirect its navigation or silently altering key values in the plane's takeoff and fuel calculations while spoofing the results on the pilot's screen--subtle changes the researchers say could potentially cause anything from runway overruns on takeoff to diversions to a different country's airspace to catastrophic crashes.

Unmanned Aerial Vehicles (UAVs) are evolving into language-interactive platforms, enabling more intuitive forms of human-drone interaction. While prior works have primarily focused on high-level planning and long-horizon navigation, we shift attention to language-guided fine-grained trajectory control, where UAVs execute short-range, reactive flight behaviors in response to language instructions. We formalize this problem as the Flying-on-a-Word (Flow) task and introduce UAV imitation learning as an effective approach. In this framework, UAVs learn fine-grained control policies by mimicking eUAxpert pilotVtrajectoriesFlopaired withwatomic Fly around the tree ahead Land on the left side of carlanguage instructions. To support this paradigm, we present UAV-Flow, the firstreal-world benchmark for language-conditioned, fine-grained UAV control.

Aircraft manufacturing is the jewel in the crown of industry, in which generating high-fidelity airfoil geometries with controllable and editable representations remains a fundamental challenge. Existing deep learning methods, which typically rely on predefined parametric representations (e.g., Bézier curves) or discrete point sets, face an inherent trade-off between expressive power and resolution adaptability. To tackle this challenge, we introduce FuncGenFoil, a novel functionspace generative model that directly reconstructs airfoil geometries as function curves. Our method inherits the advantages of arbitrary-resolution sampling and smoothness from parametric functions, as well as the strong expressiveness of discrete point-based representations. Empirical evaluations demonstrate that FuncGenFoil improves upon state-of-the-art methods in airfoil generation, achieving a relative 74.4% reduction in label error and a 23.2% increase in diversity on the AF-200K dataset. Our results highlight the advantages of function-space modeling for aerodynamic shape optimization, offering a powerful and flexible framework for high-fidelity airfoil design.

While unmanned aerial vehicles (UAVs) offer wide-area, high-altitude coverage for anomaly detection, they face challenges such as dynamic viewpoints, scale variations, and complex scenes. Existing datasets and methods, mainly designed for fixed ground-level views, struggle to adapt to these conditions, leading to significant performance drops in drone-view scenarios.To bridge this gap, we introduce A2Seek (Aerial Anomaly Seek), a large-scale, reasoning-centric benchmark dataset for aerial anomaly understanding. This dataset covers various scenarios and environmental conditions, providing high-resolution real-world aerial videos with detailed annotations, including anomaly categories, frame-level timestamps, region-level bounding boxes, and natural language explanations for causal reasoning. Building on this dataset, we propose A2Seek-R1, a novel reasoning framework that generalizes R1-style strategies to aerial anomaly understanding, enabling a deeper understanding of "Where" anomalies occur and "Why" they happen in aerial frames.To this end, A2Seek-R1 first employs a graph-of-thought (GoT)-guided supervised fine-tuning approach to activate the model's latent reasoning capabilities on A2Seek. Then, we introduce Aerial Group Relative Policy Optimization (A-GRPO) to design rule-based reward functions tailored to aerial scenarios. Furthermore, we propose a novel "seeking" mechanism that simulates UAV flight behavior by directing the model's attention to informative regions.Extensive experiments demonstrate that A2Seek-R1 achieves up to a 22.04\% improvement in AP for prediction accuracy and a 13.9\% gain in mIoU for anomaly localization, exhibiting strong generalization across complex environments and out-of-distribution scenarios. Our dataset and code are released at https://2-mo.github.io/A2Seek/.

Technology Aviation The world's largest RC Boeing 777-9X takes flight Filmmaker Tyler Perry piloted the remote-controlled behemoth, which weighs 630 pounds with a 33-foot wingspan. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. The remote-controlled aircraft is roughly the same size as a human-piloted Cessna 150. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .