Kyiv, Ukraine – Russian air defence officials could very possibly have struck an Azerbaijani passenger jet over Chechnya after panicking during a Ukrainian drone attack, analysts and experts from Ukraine, Kazakhstan and Azerbaijan have told Al Jazeera. Moscow might have also compounded what one expert described as a "crime" by not letting the damaged plane land nearby and instead forcing it to fly to Kazakhstan. The analysis by these experts comes amid mounting reports quoting unnamed Azerbaijani officials and other analysts pointing fingers at Russia for the crash, in which at least 38 people were killed. The Kremlin claimed that the AZAL 8432 flight with 67 passengers on board hit a flock of birds early Wednesday after it entered Russian airspace to land in Grozny, Chechnya's administrative capital. But within hours, photos and videos of the plane surfaced, apparently showing deep holes and multiple pockmarks on its tail.

Russian air defenses downed an Azerbaijan Airlines plane that crashed in Kazakhstan, killing 38 people, four sources with knowledge of the preliminary findings of Azerbaijan's investigation into the disaster said on Thursday. Flight J2-8243 crashed on Wednesday in a ball of fire near the city of Aktau in Kazakhstan after diverting from an area of southern Russia, where Moscow has repeatedly used air defense systems against Ukrainian drone strikes. The Embraer passenger jet had flown from Azerbaijan's capital Baku to Grozny, in Russia's southern Chechnya region, before veering off hundreds of miles across the Caspian Sea. It crashed on the opposite shore of the Caspian after what Russia's aviation watchdog said was an emergency that may have been caused by a bird strike. Officials did not explain why it had crossed the sea.

This work demonstrates universal dynamic perching capabilities for quadrotors of various sizes and on surfaces with different orientations. By employing a non-dimensionalization framework and deep reinforcement learning, we systematically assessed how robot size and surface orientation affect landing capabilities. We hypothesized that maintaining geometric proportions across different robot scales ensures consistent perching behavior, which was validated in both simulation and experimental tests. Additionally, we investigated the effects of joint stiffness and damping in the landing gear on perching behaviors and performance. While joint stiffness had minimal impact, joint damping ratios influenced landing success under vertical approaching conditions. The study also identified a critical velocity threshold necessary for successful perching, determined by the robot's maneuverability and leg geometry. Overall, this research advances robotic perching capabilities, offering insights into the role of mechanical design and scaling effects, and lays the groundwork for future drone autonomy and operational efficiency in unstructured environments.

Russia's Foreign Ministry accused NATO of trying to turn Moldova into a logistical centre to supply the Ukrainian army and of seeking to bring the Western alliance's military infrastructure closer to Russia. Arto Pahkin, the head of operations of the Finnish electricity grid, told the country's public broadcaster Yle that "the possibility of sabotage cannot be ruled out" after an undersea power cable linking Finland and Estonia broke down. It is the latest in a series of incidents involving telecom cables and energy pipelines in the Baltic Sea. A "terrorist act" sank the Russian cargo ship that went down in international waters in the Mediterranean this week, the Russian state-owned company that owns the vessel said. The Oboronlogistika company said it "thinks a targeted terrorist attack was committed on December 23, 2024, against the Ursa Major", without indicating who may have been behind the act or why. The Azerbaijan Airlines passenger jet that crashed near the city of Aktau in Kazakhstan, killing 38 people, was earlier diverting from an area of Russia that Moscow has recently defended against Ukrainian drone attacks.

An Embraer passenger jet crashed near the city of Aktau in Kazakhstan on Wednesday, killing 38 people, after diverting from an area of Russia that Moscow has recently defended against Ukrainian drone attacks. Twenty-nine survivors received hospital treatment. Azerbaijan Airlines flight J2-8243 had flown hundreds of miles off its scheduled route from Azerbaijan to Russia to crash on the opposite shore of the Caspian Sea, after what Russia's aviation watchdog said was an emergency that may have been caused by a bird strike. But an aviation expert suggested that cause seemed unlikely.

In the last decade, data-driven approaches have become popular choices for quadrotor control, thanks to their ability to facilitate the adaptation to unknown or uncertain flight conditions. Among the different data-driven paradigms, Deep Reinforcement Learning (DRL) is currently one of the most explored. However, the design of DRL agents for Micro Aerial Vehicles (MAVs) remains an open challenge. While some works have studied the output configuration of these agents (i.e., what kind of control to compute), there is no general consensus on the type of input data these approaches should employ. Multiple works simply provide the DRL agent with full state information, without questioning if this might be redundant and unnecessarily complicate the learning process, or pose superfluous constraints on the availability of such information in real platforms. In this work, we provide an in-depth benchmark analysis of different configurations of the observation space. We optimize multiple DRL agents in simulated environments with different input choices and study their robustness and their sim-to-real transfer capabilities with zero-shot adaptation. We believe that the outcomes and discussions presented in this work supported by extensive experimental results could be an important milestone in guiding future research on the development of DRL agents for aerial robot tasks.

This research investigates the efficiency of Floyd algorithm for obstacle-free path planning for autonomous aerial vehicles (UAVs) or drones. Floyd algorithm is used to generate the shortest paths for UAVs to fly from any place to the destination in a large-scale field with obstacles which UAVs cannot fly over. The simulation results demonstrated that Floyd algorithm effectively plans the shortest obstacle-free paths for UAVs to fly to a destination. It is verified that Floyd algorithm holds a time complexity of O(n3). This research revealed a correlation of a cubic polynomial relationship between the time cost and the size of the field, no correlation between the time cost and the number of obstacles, and no correlation between the time cost and the number of UAVs in the tested field. The applications of the research results are discussed in the paper as well.

Testimony and several reports have exposed unidentified flying object (UFO) sightings across the country amid the national attention on apparent drone observations over recent weeks. Luiz Elizondo, the former head of the Defense Department's Advanced Aerospace Threat Identification Program, and other witnesses testified before Congress last month about an alleged government group "hid[ing] the fact that we are not alone in the cosmos." "I believe that we as Americans can handle the truth. And I also believe the world deserves the truth," Elizondo said, urging Congress to enact legislation protecting whistleblowers too afraid to come forward. This UFO was photographed when it hovered for 15 minutes near the Holloman Air Development Center in Alamogordo, N.M., on Dec. 16, 1957. The hearing was part of a larger effort by lawmakers to investigate UFOs, or unidentified aerial phenomenon (UAPs), and determine whether elements within the government are unlawfully withholding evidence from Congress.

Israeli troops and military aircraft have killed at least eight Palestinians, including two women and a teenager, in attacks on the Tulkarem and Nur Shams refugee camps in the occupied West Bank, the Palestinian Health Ministry said. Seven people were killed in an Israeli drone attack and shooting by troops in the Tulkarem refugee camp, and one person was killed in the nearby Nur Shams camp, the Health Ministry said, following a bloody day of Israeli military raids that began at dawn on Tuesday. The ministry said that two Palestinian women – identified as Khawla Ali Abdullah Abdo, 53, and Bara Khalid Hussein, 30 – and an 18-year-old, Fathi Saeed Salem Obaid, were among the seven people killed in the Israeli attacks on Tulkarem. The official Wafa news agency reported that the teenager died after being shot in the chest and abdomen and the two women were reported killed in drone strikes. The victim in the Nur Shams camp was identified as Mahmoud Muhammad Khaled Amar, who was shot by Israeli soldiers and later found dead on the ground in the camp's Abu Bakr as-Siddiq Mosque neighbourhood, Wafa also reports.

Advanced Air Mobility (AAM) is a growing field that demands accurate modeling of legal concepts and restrictions in navigating intelligent vehicles. In addition, any implementation of AAM needs to face the challenges posed by inherently dynamic and uncertain human-inhabited spaces robustly. Nevertheless, the employment of Unmanned Aircraft Systems (UAS) beyond visual line of sight (BVLOS) is an endearing task that promises to enhance significantly today's logistics and emergency response capabilities. To tackle these challenges, we present a probabilistic and neuro-symbolic architecture to encode legal frameworks and expert knowledge over uncertain spatial relations and noisy perception in an interpretable and adaptable fashion. More specifically, we demonstrate Probabilistic Mission Design (ProMis), a system architecture that links geospatial and sensory data with declarative, Hybrid Probabilistic Logic Programs (HPLP) to reason over the agent's state space and its legality. As a result, ProMis generates Probabilistic Mission Landscapes (PML), which quantify the agent's belief that a set of mission conditions is satisfied across its navigation space. Extending prior work on ProMis' reasoning capabilities and computational characteristics, we show its integration with potent machine learning models such as Large Language Models (LLM) and Transformer-based vision models. Hence, our experiments underpin the application of ProMis with multi-modal input data and how our method applies to many important AAM scenarios.