Today, OpenAI is announcing that its technology will be deployed directly on the battlefield. The company says it will partner with the defense-tech company Anduril, a maker of AI-powered drones, radar systems, and missiles, to help US and allied forces defend against drone attacks. OpenAI will help build AI models that "rapidly synthesize time-sensitive data, reduce the burden on human operators, and improve situational awareness" to take down enemy drones, according to the announcement. Specifics have not been released, but the program will be narrowly focused on defending US personnel and facilities from unmanned aerial threats, according to Liz Bourgeois, an OpenAI spokesperson. "This partnership is consistent with our policies and does not involve leveraging our technology to develop systems designed to harm others," she said.

A robot that can jump into flight like a bird could eliminate the need for runways for small fixed-winged drones. Birds use the powerful explosive force generated by their legs to leap into the air and start flying, but building a robot that can withstand the strong acceleration and forces involved in doing that has proved difficult. Now, Won Dong Shin at the Swiss Federal Technology Institute of Lausanne (EPFL) and his colleagues have built a flying propellered robot called RAVEN that can walk, hop and jump into the air to start flying, with legs that work like a bird's. "Fixed-wing vehicles, like airplanes, always require a runway or a launcher, which is not found everywhere. It really requires designated infrastructure to make an airplane take off," says Shin. "But if you see a bird, they just walk around, jump and take off. They don't need any external assistance."

Path Planning methods for autonomously controlling swarms of unmanned aerial vehicles (UAVs) are gaining momentum due to their operational advantages. An increasing number of scenarios now require autonomous control of multiple UAVs, as autonomous operation can significantly reduce labor costs. Additionally, obtaining optimal flight paths can lower energy consumption, thereby extending battery life for other critical operations. Many of these scenarios, however, involve obstacles such as power lines and trees, which complicate Path Planning. This paper presents an evolutionary computation-based system employing genetic algorithms to address this problem in environments with obstacles. The proposed approach aims to ensure complete coverage of areas with fixed obstacles, such as in field exploration tasks, while minimizing flight time regardless of map size or the number of UAVs in the swarm. No specific goal points or prior information beyond the provided map is required. The experiments conducted in this study used five maps of varying sizes and obstacle densities, as well as a control map without obstacles, with different numbers of UAVs. The results demonstrate that this method can determine optimal paths for all UAVs during full map traversal, thus minimizing resource consumption. A comparative analysis with other state-of-the-art approach is presented to highlight the advantages and potential limitations of the proposed method.

The FBI has launched an investigation into mysterious glowing lights that have been spotted over New Jersey for the last few weeks. Eyewitnesses reported unexplained'car-sized' drones over the Trump National Golf Club in Bedminster and the Picatinny Arsenal Military Base in Rockaway, among other locations throughout northern New Jersey. Video footage revealed the drones featured green and red lights on their wings and multiple eyewitness described them as large as a small car. However, the flying objects are larger than drones used by hobbyists, raising questions about their proximity to those specific locations. The Federal Aviation Administration (FAA) was first alerted about the strange activity in Morris County, where the military base is located, on November 18, but sights also surfaced in nearby Menham, Chester and Morristown.

Fox News' Stephanie Bennett reports the latest on the unidentified drones from London. The Federal Aviation Administration (FAA) confirmed Tuesday it issued two flight restrictions following questionable drone activity in the area of President-elect Trump's New Jersey golf club. On Nov. 18, the FAA first received reports of drone activity within Morris County, the border of which lies about two miles north of Trump National Golf Club Bedminster in Somerset County. Upon request from "federal security partners," the agency issued two TFRs, or temporary flight restrictions, and several reports of drone sightings continued into this week in Central Jersey. One restriction covers an area near Solberg-Hunterdon County Airport that consists of airspace above Trump Bedminster.

An Israeli drone strike has killed one person in southern Lebanon, according to Lebanese health authorities, as Prime Minister Benjamin Netanyahu promised to enforce the ceasefire with Hezbollah "with an iron fist". Lebanon's Ministry of Public Health and state media said Israeli forces carried out several new drone and artillery strikes in southern Lebanon on Tuesday, putting further strain on a tenuous 6-day-old ceasefire with Hezbollah. "An Israeli enemy drone strike on the town of Shebaa killed one person," a Health Ministry statement said. The state-run National News Agency (NNA) described the man who was killed as a "shepherd". The new attacks come as Israeli officials threatened to expand attacks on Lebanon if the ceasefire with the Lebanese armed group Hezbollah collapses.

A Florida man allegedly broke into a woman's home, stabbed her while she was sleeping and attempted to flee from deputies. A Florida man is facing charges after he allegedly broke into a woman's home, stabbed her while she was sleeping and attempted to run away from deputies. Bonnier Jose Sarmiento Lanza, 33, on Sunday broke into a woman's home on New York Drive in Tice, Florida, and stabbed her multiple times while she was sleeping, according to the Lee County Sheriff's Office. Lanza also hit another person inside the home before fleeing the scene. Bonnier Jose Sarmiento Lanza, 33, is charged with two counts of burglary with battery and aggravated battery with a deadly weapon.

A squadron of six Chinese Chengdu J-10 jets took off towards an overcast sky in front of thousands of spectators at an airfield in southern China's coastal city of Zhuhai in mid-November. Flying low in a close V-shaped formation, the jets circled back and as they approached a cluster of buildings near the spectators, trails of red, blue, yellow and white smoke suddenly poured from each plane, bringing a cheer from onlookers that was almost as loud as the roar from the warplanes' engines. Seconds later, the J-10s broke their close formation to show off a series of even more impressive acrobatic manoeuvres. But the aerial show by the seasoned pilots was far from the only demonstration of prowess at the China International Aviation & Aerospace Exhibition, better known as Airshow China or the Zhuhai Airshow, which is held biennially and named after the city in southern China where it is held. A wide array of new equipment and aircraft available to the Chinese military – known as the People's Liberation Army (PLA) – was unveiled for the first time at the airshow, held from November 12 to 17.

Modern unmanned aerial vehicles (UAVs) are irreplaceable in search and rescue (SAR) missions to obtain a situational overview or provide closeups without endangering personnel. However, UAVs heavily rely on global navigation satellite system (GNSS) for localization which works well in open spaces, but the precision drastically degrades in the vicinity of buildings. These inaccuracies hinder aggregation of diverse data from multiple sources in a unified georeferenced frame for SAR operators. In contrast, CityGML models provide approximate building shapes with accurate georeferenced poses. Besides, LiDAR works best in the vicinity of 3D structures. Hence, we refine coarse GNSS measurements by registering LiDAR maps against CityGML and digital elevation map (DEM) models as a prior for allocentric mapping. An intuitive plausibility score selects the best hypothesis based on occupancy using a 2D height map. Afterwards, we integrate the registration results in a continuous-time spline-based pose graph optimizer with LiDAR odometry and further sensing modalities to obtain globally consistent, georeferenced trajectories and maps. We evaluate the viability of our approach on multiple flights captured at two distinct testing sites. Our method successfully reduced GNSS offset errors from up-to 16 m to below 0.5 m on multiple flights. Furthermore, we obtain globally consistent maps w.r.t. prior 3D geospatial models.

The human-robot interaction (HRI) is a growing area of research. In HRI, complex command (action) classification is still an open problem that usually prevents the real applicability of such a technique. The literature presents some works that use neural networks to detect these actions. However, occlusion is still a major issue in HRI, especially when using uncrewed aerial vehicles (UAVs), since, during the robot's movement, the human operator is often out of the robot's field of view. Furthermore, in multi-robot scenarios, distributed training is also an open problem. In this sense, this work proposes an action recognition and control approach based on Long Short-Term Memory (LSTM) Deep Neural Networks with two layers in association with three densely connected layers and Federated Learning (FL) embedded in multiple drones. The FL enabled our approach to be trained in a distributed fashion, i.e., access to data without the need for cloud or other repositories, which facilitates the multi-robot system's learning. Furthermore, our multi-robot approach results also prevented occlusion situations, with experiments with real robots achieving an accuracy greater than 96%.