Fox News correspondent Alex Hogan reports from Kyiv, Ukraine on Russian attacks on civilian areas in the Donbas region this week on'America Reports.' Russia's naval headquarters for its Black Sea fleet in Ukraine's occupied Crimea was hit by a drone Saturday, a Russian official said. The Moscow installed governor of Sevastopol, Mikhail Razvozhayev, took to Telegram to confirm the hit and said a drone crashed into the roof of the building. There were no reported casualities. Razvozhayev first said the drone "flew into the roof" of the building and noted that Russian forces had not been able to down the strike. FILE - Russian Navy ships are docked in the Sevastopol bay on March 4, 2014.

Drones that fly packages straight to people's doors could be an environmentally friendly alternative to conventional modes of transportation. A study comparing the environmental impact of various'last-mile' delivery methods -- which take a package on the final leg of its journey -- finds that greenhouse-gas emissions per parcel were 84% lower for drones than for diesel trucks. Drones also consumed up to 94% less energy per parcel than did the trucks. The research, published on 5 August in the journal Patterns, indicates that using drones to deliver medication and other small items could cut the environmental impact of product deliveries. Major companies such as Amazon have been experimenting with using drones and robots to deliver packages with an eye to reducing their environmental impact.

Military drones are now everywhere. Of course, the capabilities of these machines are not the same, and the top-range models greatly outperform their lower-tier rivals. Simple remotely-operated robots and unmanned aerial vehicles are controlled by a human operator. Human decides what this military machine must do, even when conducting a simple reconnaissance operation, or dropping grenades through an open hatch on a tank's turret. But today we already have combat drones that can operate entirely on their own. This means they can recognize and engage their targets autonomously.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Texas prison inmate serving time for robbery and burglary now faces federal charges in connection with using a drone to make prison yard drops to smuggle drugs and contraband into a correctional facility. Yeshmel James Wright, 35, of Dallas, is charged with conspiracy to possess with intent to distribute methamphetamine and conspiracy to possess with intent to distribute synthetic marijuana. Other prohibited items he attempted to smuggle inside prisons include cell phones, authorities said.

It's been less than four months since Snap unveiled a selfie drone called Pixy, but it seems the company is already giving up on the device. CEO Evan Spiegel told employees that Snap is halting further work on Pixy amid a reprioritization of resources, according to The Wall Street Journal. The $250 drone can take off from and land in your hand. It has four preset flight paths and can capture photos and videos that you can transfer to and share on Snapchat. For now, at least, Pixy is still available to buy from Snap's website.

"This is a war of artillery, high-tech weapons and minds. The soldier still plays an important role but success is mostly dependent on rockets, artillery and air strikes," says Maj Gen Dmytro Marchenko, who successfully organised the defence of the southern city of Mykolaiv from Russian attack last spring. It is not like World War Two, when one big army attacked another, he argues.

Ukraine's drone pilots under fire as they locate Russian targets

There are many facets and levels of drone education. We will focus on the best educational drones for beginner pilots, perhaps best for children. Drones like the UVify OOri and the Ryze Tello have proper education programs centered around them. These platforms teach you some drone hardware basics, then promote critical thinking as you code flight features for the drone. The basics of flight are covered, the machine will hover in place, but you tell it where to go in the sky, just watch out for that wall.

High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic congestion. However, air delivery service will not scale up without proper traffic management for drones in dense urban environment. Currently, a range of Concepts of Operations (ConOps) for unmanned aircraft system traffic management (UTM) are being proposed and evaluated by researchers, operators, and regulators. Among these, the tube-based (or corridor-based) ConOps has emerged in operations in some regions of the world for drone deliveries and is expected to continue serving certain scenarios that with dense and complex airspace and requires centralized control in the future. Towards the tube-based ConOps, we develop a route network planning method to design routes (tubes) in a complex urban environment in this paper. In this method, we propose a priority structure to decouple the network planning problem, which is NP-hard, into single-path planning problems. We also introduce a novel space cost function to enable the design of dense and aligned routes in a network. The proposed method is tested on various scenarios and compared with other state-of-the-art methods. Results show that our method can generate near-optimal route networks with significant computational time-savings.

A multi-robot system (MRS) is a group of coordinated robots designed to cooperate with each other and accomplish given tasks. Due to the uncertainties in operating environments, the system may encounter emergencies, such as unobserved obstacles, moving vehicles, and extreme weather. Animal groups such as bee colonies initiate collective emergency reaction behaviors such as bypassing obstacles and avoiding predators, similar to muscle-conditioned reflex which organizes local muscles to avoid hazards in the first response without delaying passage through the brain. Inspired by this, we develop a similar collective conditioned reflex mechanism for multi-robot systems to respond to emergencies. In this study, Collective Conditioned Reflex (CCR), a bio-inspired emergency reaction mechanism, is developed based on animal collective behavior analysis and multi-agent reinforcement learning (MARL). The algorithm uses a physical model to determine if the robots are experiencing an emergency; then, rewards for robots involved in the emergency are augmented with corresponding heuristic rewards, which evaluate emergency magnitudes and consequences and decide local robots' participation. CCR is validated on three typical emergency scenarios: \textit{turbulence, strong wind, and hidden obstacle}. Simulation results demonstrate that CCR improves robot teams' emergency reaction capability with faster reaction speed and safer trajectory adjustment compared with baseline methods.