Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Emergency response officials said at least 85 people have been confirmed dead after a "mistaken" army drone attack on a religious gathering in northwest Nigeria. The victims were killed Sunday night by drones "targeting terrorists and bandits" in Kaduna state's Tudun Biri village, according to government and security officials. They were observing a Muslim holiday.

The deputy commander of Russia's 14th Army Corps, Major-General Vladimir Zavadsky, has been killed in Ukraine, a top regional official confirmed. Zavadsky died "at a combat post in the special operation zone", Alexander Gusev, the governor of Russia's Voronezh region, said on Monday without providing any further details. The "special military operation" is the term Russia uses to describe the war in Ukraine, which it launched in February 2022. Gusev paid tribute to Zavadsky, calling him "a courageous officer, a real general and a worthy man". Zavadsky's death marked the seventh major-general confirmed dead by Russia, making him the 12th senior officer reported deceased since the onset of the war, investigative news outlet iStories reported. Meanwhile, on Tuesday, Ukrainian authorities reported that their military successfully downed 10 out of 17 attack drones launched by Russia overnight.

A Nigerian military attack that used drones to target rebels instead killed at least 85 civilians gathered for a religious celebration, authorities said Monday. The attack was the latest in recent errant bombings of residents in Nigeria's troubled regions; between February 2014 when a Nigerian military aircraft dropped a bomb on Daglun in Borno state killing 20 civilians and September 2022, there were at least 14 documented incidences of such bombings in residential areas. The attack on Sunday night in Tudun Biri village of Kaduna state's Igabi council area took place as Muslims gathered there to observe the holiday celebrating the birthday of the Prophet Muhammad. Kaduna Governor Uba Sani said civilians were "mistakenly killed and many others were wounded" by a drone "targeting terrorists and bandits". The National Emergency Management Agency said in a statement on Tuesday that "85 dead bodies have so far been buried while search is still ongoing".

The increasing spreading of small commercial Unmanned Aerial Vehicles (UAVs, aka drones) presents serious threats for critical areas such as airports, power plants, governmental and military facilities. In fact, such UAVs can easily disturb or jam radio communications, collide with other flying objects, perform espionage activity, and carry offensive payloads, e.g., weapons or explosives. A central problem when designing surveillance solutions for the localization of unauthorized UAVs in critical areas is to decide how many triangulating sensors to use, and where to deploy them to optimise both coverage and cost effectiveness. In this article, we compute deployments of triangulating sensors for UAV localization, optimizing a given blend of metrics, namely: coverage under multiple sensing quality levels, cost-effectiveness, fault-tolerance. We focus on large, complex 3D regions, which exhibit obstacles (e.g., buildings), varying terrain elevation, different coverage priorities, constraints on possible sensors placement. Our novel approach relies on computational geometry and statistical model checking, and enables the effective use of off-the-shelf AI-based black-box optimizers. Moreover, our method allows us to compute a closed-form, analytical representation of the region uncovered by a sensor deployment, which provides the means for rigorous, formal certification of the quality of the latter. We show the practical feasibility of our approach by computing optimal sensor deployments for UAV localization in two large, complex 3D critical regions, the Rome Leonardo Da Vinci International Airport (FCO) and the Vienna International Center (VIC), using NOMAD as our state-of-the-art underlying optimization engine. Results show that we can compute optimal sensor deployments within a few hours on a standard workstation and within minutes on a small parallel infrastructure.

In this paper, we propose an alternating optimization method to address a time-optimal trajectory generation problem. Different from the existing solutions, our approach introduces a new formulation that minimizes the overall trajectory running time while maintaining the polynomial smoothness constraints and incorporating hard limits on motion derivatives to ensure feasibility. To address this problem, an alternating peak-optimization method is developed, which splits the optimization process into two sub-optimizations: the first sub-optimization optimizes polynomial coefficients for smoothness, and the second sub-optimization adjusts the time allocated to each trajectory segment. These are alternated until a feasible minimum-time solution is found. We offer a comprehensive set of simulations and experiments to showcase the superior performance of our approach in comparison to existing methods. A collection of demonstration videos with real drone flying experiments can be accessed at https://www.youtube.com/playlist?list=PLQGtPFK17zUYkwFT-fr0a8E49R8Uq712l .

Research on Multi-rotor Aerial Vehicles (MAVs) has experienced remarkable advancements over the past two decades, propelling the field forward at an accelerated pace. Through the implementation of motion control and the integration of specialized mechanisms, researchers have unlocked the potential of MAVs to perform a wide range of tasks in diverse scenarios. Notably, the literature has highlighted the distinctive attributes of MAVs that endow them with a competitive edge in physical interaction when compared to other robotic systems. In this survey, we present a categorization of the various types of physical interactions in which MAVs are involved, supported by comprehensive case studies. We examine the approaches employed by researchers to address different challenges using MAVs and their applications, including the development of different types of controllers to handle uncertainties inherent in these interactions. By conducting a thorough analysis of the strengths and limitations associated with different methodologies, as well as engaging in discussions about potential enhancements, this survey aims to illuminate the path for future research focusing on MAVs with high actuation capabilities.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Nigerian military attack that used drones to target rebels instead killed some civilians, government and military officials said Monday. The misfire during a religious celebration was the latest such errant bombing of local residents in Nigeria's violence hot spots. Muslims observing Maulud on Sunday night in Kaduna state's Igabi council area were "mistakenly killed and many others injured" by the drone "targeting terrorists and bandits," Gov. Uba Sani said.

FOX News White House correspondent Peter Doocy has the latest on the Biden administration's response to the Middle East conflict on'Special Report.' As Israeli Defense Forces resumed military operations to eradicate the Hamas terrorist threat last Friday, the Biden administration is inserting itself into Israel's war planning process, teaching the Israelis – who've been fighting for their survival for decades – how to properly prosecute the conflict. Washington warfare "experts" – who arguably haven't secured a single clear military victory since 1945 – insist that Israeli military strategists alter their war plans to make their combat operations more targeted and their strikes more accurate, in order to minimize casualties, especially among civilians. The Biden administration's demands, while noble-sounding, are misguided and unreasonable. Implementing these requirements, at the expense of achieving the main mission of eliminating Hamas and its entire supporting infrastructure, will likely prolong the conflict, ultimately resulting in many more Israeli and Palestinian deaths.

US Central Command, known as Centcom said that, on Sunday morning, the USS Carney detected an anti-ship ballistic missile exploding near the Unity Explorer, a Bahamian-flagged, UK-owned and operated cargo ship.

Formation flight is when multiple objects fly together in a coordination. Various automatic control methods have been used for the autonomous execution of formation flight of aerial vehicles. In this paper, the capacity of the model predictive control (MPC) approach in the autonomous execution of formation flight is examined. The MPC is a controller that capable of performing formation flight, maintaining tracking desired trajectory while avoiding collisions between aerial vehicles, and obstacles faced. Through this approach, aerial vehicle models with six degrees of freedom in a three-dimensional environment are performed formation flight autonomously, mostly in a triangle order. Not only the trajectory for the formation flight can be tracked through the MPC architecture, also the collision avoidance strategies of the aerial vehicles can be performed by this architecture. Simulation studies show that MPC has sufficient capability in both cases. Therefore, it is concluded that this method can deal with constraints, avoid obstacles as well as collisions between aerial vehicles. However, implementation of MPC to aerial vehicles in real time holds challenges.