Air raid sirens have blared across the Ukrainian capital, Kyiv, as Russia kept pounding the city for a second night in a row. The drone attacks early on Monday targeted critical infrastructure in Kyiv and the surrounding region, according to Ukrainian officials, and have wounded at least one person. "It is loud in the region and in the capital: night drone attacks," said Oleksiy Kuleba, the governor of the Kyiv region. "Russians launched several waves of [Iranian-made] Shahed drones. Targeting critical infrastructure facilities," he wrote on the Telegram messaging application.

Russia has been targeting Ukraine's energy infrastructure for several months, destroying power stations and plunging millions into darkness during the country's freezing winter.

Hybrid unmanned aerial vehicles (UAVs) integrate the efficient forward flight of fixed-wing and vertical takeoff and landing (VTOL) capabilities of multicopter UAVs. This paper presents the modeling, control and simulation of a new type of hybrid micro-small UAVs, coined as lifting-wing quadcopters. The airframe orientation of the lifting wing needs to tilt a specific angle often within $ 45$ degrees, neither nearly $ 90$ nor approximately $ 0$ degrees. Compared with some convertiplane and tail-sitter UAVs, the lifting-wing quadcopter has a highly reliable structure, robust wind resistance, low cruise speed and reliable transition flight, making it potential to work fully-autonomous outdoor or some confined airspace indoor. In the modeling part, forces and moments generated by both lifting wing and rotors are considered. Based on the established model, a unified controller for the full flight phase is designed. The controller has the capability of uniformly treating the hovering and forward flight, and enables a continuous transition between two modes, depending on the velocity command. What is more, by taking rotor thrust and aerodynamic force under consideration simultaneously, a control allocation based on optimization is utilized to realize cooperative control for energy saving. Finally, comprehensive Hardware-In-the-Loop (HIL) simulations are performed to verify the advantages of the designed aircraft and the proposed controller.

Enabling vertical take-off and landing while providing the ability to fly long ranges opens the door to a wide range of new real-world aircraft applications while improving many existing tasks. Tiltrotor vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) are a better choice than fixed-wing and multirotor aircraft for such applications. Prior works on these aircraft have addressed aerodynamic performance, design, modeling, and control. However, a less explored area is the study of their potential fault tolerance due to their inherent redundancy, which allows them to tolerate some degree of actuation failure. This paper introduces tolerance to several types of actuator failures in a tiltrotor VTOL aircraft. We discuss the design and modeling of a custom tiltrotor VTOL UAV, which is a combination of a fixed-wing aircraft and a quadrotor with tilting rotors, where the four propellers can be rotated individually. Then, we analyze the feasible wrench space the vehicle can generate and design the dynamic control allocation so that the system can adapt to actuator failures, benefiting from the configuration redundancy. The proposed approach is lightweight and is implemented as an extension to an already-existing flight control stack. Extensive experiments validate that the system can maintain the controlled flight under different actuator failures. To the best of our knowledge, this work is the first study of the tiltrotor VTOL's fault-tolerance that exploits the configuration redundancy. The source code and simulation can be accessed at https://theairlab.org/vtol.

Unmanned aerial vehicle (UAV) swarms are considered as a promising technique for next-generation communication networks due to their flexibility, mobility, low cost, and the ability to collaboratively and autonomously provide services. Distributed learning (DL) enables UAV swarms to intelligently provide communication services, multi-directional remote surveillance, and target tracking. In this survey, we first introduce several popular DL algorithms such as federated learning (FL), multi-agent Reinforcement Learning (MARL), distributed inference, and split learning, and present a comprehensive overview of their applications for UAV swarms, such as trajectory design, power control, wireless resource allocation, user assignment, perception, and satellite communications. Then, we present several state-of-the-art applications of UAV swarms in wireless communication systems, such us reconfigurable intelligent surface (RIS), virtual reality (VR), semantic communications, and discuss the problems and challenges that DL-enabled UAV swarms can solve in these applications. Finally, we describe open problems of using DL in UAV swarms and future research directions of DL enabled UAV swarms. In summary, this survey provides a comprehensive survey of various DL applications for UAV swarms in extensive scenarios.

Russia's New Year assault on Ukraine left three people dead and wounded another 50 as Moscow on Sunday claimed to have thwarted Kyiv's "terror attacks" on the homeland. The Ukrainian capital and other cities came under fire from missiles and Iranian-made drones. The Ukrainian air force said Sunday 45 Iranian-made drones had been destroyed overnight. Thirteen were shot down at the end of 2022 and another 32 after midnight, the air force said. Andriy Nebitov, the head of the Kyiv police, posted on Facebook a picture of wreckage of a downed drone that featured the words "Happy New Year" in Russian.

Abstract: The rapid development of technology has brought unmanned aerial vehicles (UAVs) to become widely known in the current era. The market of UAVs is also predicted to continue growing with related technologies in the future. UAVs have been used in various sectors, including livestock, forestry, and agriculture. In agricultural applications, UAVs are highly capable of increasing the productivity of the farm and reducing farmers' workload. This study examines the urgency of UAV implementation in the agriculture sector. A short history of UAVs is provided in this paper to portray the development of UAVs from time to time. The classification of UAVs is also discussed to differentiate various types of UAVs. The application of UAVs in spraying and crop monitoring is based on the previous studies that have been done by many scientific groups and researchers who are working closely to propose solutions for agriculture-related issues. Furthermore, the limitations of UAV applications are also identified. The challenges in implementing agricultural UAVs in Indonesia are also presented. Keywords: Unmanned aerial vehicle, agricultural UAV, spraying, crop monitoring. 1. Introduction According to the United Nations (UN), the world population is projected to reach 9.7 billion people in 2050 (UN, 2015). This vast population would potentially double the food demand in the future (Hunter et al., 2017). Consequently, the ever-growing population that would emerge could cause food shortages in the future. This issue has become a severe problem since the Food and Agriculture Organization (FAO) announced similar speculation in which the current agricultural production must be increased by 70 percent by 2050 to meet the increasing demand for highquality food (Mundial, 2021). Many people suffering from hunger become a signal of how severe the food shortage is, and it was reported that more than 820 million people in 2018 were considered undernutrition (WHO, 2019). Surprisingly, the earlier data mentioned shows the increasing tendency towards people suffering from hunger since only around 690 million people were considered suffering from hunger in 2015.

According to the rapid development of drone technologies, drones are widely used in many applications including military domains. In this paper, a novel situation-aware DRL- based autonomous nonlinear drone mobility control algorithm in cyber-physical loitering munition applications. On the battlefield, the design of DRL-based autonomous control algorithm is not straightforward because real-world data gathering is generally not available. Therefore, the approach in this paper is that cyber-physical virtual environment is constructed with Unity environment. Based on the virtual cyber-physical battlefield scenarios, a DRL-based automated nonlinear drone mobility control algorithm can be designed, evaluated, and visualized. Moreover, many obstacles exist which is harmful for linear trajectory control in real-world battlefield scenarios. Thus, our proposed autonomous nonlinear drone mobility control algorithm utilizes situation-aware components those are implemented with a Raycast function in Unity virtual scenarios. Based on the gathered situation-aware information, the drone can autonomously and nonlinearly adjust its trajectory during flight. Therefore, this approach is obviously beneficial for avoiding obstacles in obstacle-deployed battlefields. Our visualization-based performance evaluation shows that the proposed algorithm is superior from the other linear mobility control algorithms.

The vision of unmanned aerial vehicles is very significant for UAV-related applications such as search and rescue, landing on a moving platform, etc. In this work, we have developed an integrated system for the UAV landing on the moving platform, and the UAV object detection with tracking in the complicated environment. Firstly, we have proposed a robust LoG-based deep neural network for object detection and tracking, which has great advantages in robustness to object scale and illuminations compared with typical deep network-based approaches. Then, we have also improved based on the original Kalman filter and designed an iterative multi-model-based filter to tackle the problem of unknown dynamics in real circumstances of motion estimations. Next, we implemented the whole system and do ROS Gazebo-based testing in two complicated circumstances to verify the effectiveness of our design. Finally, we have deployed the proposed detection, tracking, and motion estimation strategies into real applications to do UAV tracking of a pillar and obstacle avoidance. It is demonstrated that our system shows great accuracy and robustness in real applications.

David Bellavia, Dr. Richard Jadick, and Ozzie Martinez Jr. weigh in on the intensifying war in Ukraine after Russia fired more than 100 missiles. They also reflect on the military's efforts in the Battle of Fallujah. Russia will deploy violent soccer fans, known as "hooligans" or "ultras," to Ukraine in an effort to bolster troop numbers as the conflict enters its 11th month. "What is very clear is that Putin will not end this war any time soon," Rebekah Koffler, president of Doctrine & Strategy Consulting and a former DIA intelligence officer, told Fox News Digital. "He will use hooligans, prisoners, and any sort of thug to continue flowing fighters into Ukraine, to keep it from becoming part of NATO. The mission is this important."