Drones
'Massive' Russian attack on Ukraine's Kyiv kills at least 4, dozens hurt
An overnight Russian drone and missile attack on Ukraine's capital Kyiv has killed at least four people and wounded more than 20 others, officials said. Powerful explosions rocked the city into the early hours of Thursday morning, illuminating the sky and leaving behind columns of smoke as Russian projectiles damaged and destroyed buildings in several districts of the city. The attack was the first major combined Russian drone and missile attack to strike Kyiv since United States President Donald Trump met with Russian President Vladimir Putin in Alaska earlier this month to discuss ending the war in Ukraine. Tymur Tkachenko, the head of Kyiv's city military administration, said a 14-year-old girl was among those reported killed, citing preliminary information. A five-storey residential building in the city's Darnytskyi district was hit directly.
Watch: Moment pilot is rescued after emergency water landing
New drone video shows the moment pilot Mark Finkelstein was rescued after making an emergency water landing off the coast of Oak Island Pier in North Carolina. The personal aircraft experienced engine failure, according to Finkelstein. Rescuers, who were already in the area responding to a nearby call, are seen rushing to the small plane and extracting Finkelstein in less than 30 seconds. The rescue footage was released on 27 August after officials from the Federal Aviation Administration finished their investigation.
Embodied Intelligence for Sustainable Flight: A Soaring Robot with Active Morphological Control
Elmkaiel, Ghadeer, Schmitt, Syn, Muehlebach, Michael
Achieving both agile maneuverability and high energy efficiency in aerial robots, particularly in dynamic wind environments, remains challenging. Conventional thruster-powered systems offer agility but suffer from high energy consumption, while fixed-wing designs are efficient but lack hovering and maneuvering capabilities. We present Floaty, a shape-changing robot that overcomes these limitations by passively soaring, harnessing wind energy through intelligent morphological control inspired by birds. Floaty's design is optimized for passive stability, and its control policy is derived from an experimentally learned aerodynamic model, enabling precise attitude and position control without active propulsion. Wind tunnel experiments demonstrate Floaty's ability to hover, maneuver, and reject disturbances in vertical airflows up to 10 m/s. Crucially, Floaty achieves this with a specific power consumption of 10 W/kg, an order of magnitude lower than thruster-powered systems. This introduces a paradigm for energy-efficient aerial robotics, leveraging morphological intelligence and control to operate sustainably in challenging wind conditions.
Mount Everest has a poo problem. Are drones the answer?
Breakthroughs, discoveries, and DIY tips sent every weekday. For some adventurers, scaling Mount Everest represents the ultimate test of grit and determination: a visual signifier of humanity's epic struggle to overcome the elements. For others, the peak can seem more like a really tall trash can. Every year, around 600 climbers make the trek from the mountain's base camp to the summit. During their time on Everest, each person produces an estimated 18 pounds of waste, most of which is left behind.
Pentagon baffled by 8,000 mysterious UFO orbs hovering over US military bases
An invasion of small metallic orbs has been spotted hovering over the US in recent years, leaving the Pentagon scrambling to identify these mysterious UFOs. A new report from the crowdsourced platform Enigma, which allows people to report sightings of unidentified flying objects (UFOs), reveals more than 8,000 sightings across the US between December 2022 and June 2025. Among these, 422 reports specifically describe metallic orbs, with the majority observed between 1am and 4am near military installations in New York, California, and Arizona. Eyewitnesses, including civilians, pilots, and military personnel, reported seeing the spheres hover silently before moving at extreme speeds, leaving no trace of their departure. Some of the sightings have been captured on video or radar, though many remain unexplained.
Russian drone attacks cause massive power cuts, Ukraine says
In his post on Wednesday, Zelensky said Russia had carried out almost 100 drone attacks overnight. Energy facilities were the main targets, but a school in the Kharkiv region and a high-rise building in Kherson were also hit, he said. "New steps are needed to put pressure on Russia to stop the strikes and truly guarantee security. We are working with partners for such pressure," Zelensky added. Three and a half years after Russia's full-scale invasion of Ukraine, fighting on the ground shows no sign of abating.
AI drone finds missing hiker's remains in mountains after 10 months
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A missing hiker's dead body was finally found in July in Italy's rugged Piedmont region after 10 months. The recovery team credited the breakthrough to an AI-powered drone that spotted a critical clue within hours. The same process would have taken weeks or even months if done by the human eye.
Enhanced UAV Path Planning Using the Tangent Intersection Guidance (TIG) Algorithm
Cheriet, Hichem, Badra, Khellat Kihel, Samira, Chouraqui
Efficient and safe navigation of Unmanned Aerial Vehicles (UAVs) is critical for various applications, including combat support, package delivery and Search and Rescue Operations. This paper introduces the Tangent Intersection Guidance (TIG) algorithm, an advanced approach for UAV path planning in both static and dynamic environments. The algorithm uses the elliptic tangent intersection method to generate feasible paths. It generates two sub-paths for each threat, selects the optimal route based on a heuristic rule, and iteratively refines the path until the target is reached. Considering the UAV kinematic and dynamic constraints, a modified smoothing technique based on quadratic Bézier curves is adopted to generate a smooth and efficient route. Experimental results show that the TIG algorithm can generate the shortest path in less time, starting from 0.01 seconds, with fewer turning angles compared to A*, PRM, RRT*, Tangent Graph, and Static APPATT algorithms in static environments. Furthermore, in completely unknown and partially known environments, TIG demonstrates efficient real-time path planning capabilities for collision avoidance, outperforming APF and Dynamic APPATT algorithms.
Learning Real-World Acrobatic Flight from Human Preferences
Merk, Colin, Geles, Ismail, Xing, Jiaxu, Romero, Angel, Ramponi, Giorgia, Scaramuzza, Davide
Preference-based reinforcement learning (PbRL) enables agents to learn control policies without requiring manually designed reward functions, making it well-suited for tasks where objectives are difficult to formalize or inherently subjective. Acrobatic flight poses a particularly challenging problem due to its complex dynamics, rapid movements, and the importance of precise execution. In this work, we explore the use of PbRL for agile drone control, focusing on the execution of dynamic maneuvers such as powerloops. Building on Preference-based Proximal Policy Optimization (Preference PPO), we propose Reward Ensemble under Confidence (REC), an extension to the reward learning objective that improves preference modeling and learning stability. Our method achieves 88.4% of the shaped reward performance, compared to 55.2% with standard Preference PPO. We train policies in simulation and successfully transfer them to real-world drones, demonstrating multiple acrobatic maneuvers where human preferences emphasize stylistic qualities of motion. Furthermore, we demonstrate the applicability of our probabilistic reward model in a representative MuJoCo environment for continuous control. Finally, we highlight the limitations of manually designed rewards, observing only 60.7% agreement with human preferences. These results underscore the effectiveness of PbRL in capturing complex, human-centered objectives across both physical and simulated domains.
Data-Driven Discovery and Formulation Refines the Quasi-Steady Model of Flapping-Wing Aerodynamics
Kamimizu, Yu, Liu, Hao, Nakata, Toshiyuki
Insects control unsteady aerodynamic forces on flapping wings to navigate complex environments. While understanding these forces is vital for biology, physics, and engineering, existing evaluation methods face trade-offs: high-fidelity simulations are computationally or experimentally expensive and lack explanatory power, whereas theoretical models based on quasi-steady assumptions offer insights but exhibit low accuracy. To overcome these limitations and thus enhance the accuracy of quasi-steady aerodynamic models, we applied a data-driven approach involving discovery and formulation of previously overlooked critical mechanisms. Through selection from 5,000 candidate kinematic functions, we identified mathematical expressions for three key additional mechanisms -- the effect of advance ratio, effect of spanwise kinematic velocity, and rotational Wagner effect -- which had been qualitatively recognized but were not formulated. Incorporating these mechanisms considerably reduced the prediction errors of the quasi-steady model using the computational fluid dynamics results as the ground truth, both in hawkmoth forward flight (at high Reynolds numbers) and fruit fly maneuvers (at low Reynolds numbers). The data-driven quasi-steady model enables rapid aerodynamic analysis, serving as a practical tool for understanding evolutionary adaptations in insect flight and developing bio-inspired flying robots.