Terahertz (THz) unmanned aerial vehicle (UAV) networks with flexible topologies and ultra-high data rates are expected to empower numerous applications in security surveillance, disaster response, and environmental monitoring, among others. However, the dynamic topologies hinder the efficient long-term joint power and antenna array resource allocation for THz links among UAVs. Furthermore, the continuous nature of power and the discrete nature of antennas cause this joint resource allocation problem to be a mixed-integer nonlinear programming (MINLP) problem with non-convexity and NP-hardness. Inspired by recent rapid advancements in deep reinforcement learning (DRL), a graph neural network (GNN) aided DRL algorithm for resource allocation in the dynamic THz UAV network with an emphasis on self-node features (GLOVE) is proposed in this paper, with the aim of resource efficiency (RE) maximization. When training the allocation policy for each UAV, GLOVE learns the relationship between this UAV and its neighboring UAVs via GNN, while also emphasizing the important self-node features of this UAV. In addition, a multi-task structure is leveraged by GLOVE to cooperatively train resource allocation decisions for the power and sub-arrays of all UAVs. Experimental results illustrate that GLOVE outperforms benchmark schemes in terms of the highest RE and the lowest latency. Moreover, unlike the benchmark methods with severe packet loss, GLOVE maintains zero packet loss during the entire training process, demonstrating its better robustness under the highly dynamic THz UAV network.

--The miniaturisation of sensors and processors, the advancements in connected edge intelligence, and the exponential interest in Artificial Intelligence are boosting the affirmation of autonomous nano-size drones in the Internet of Robotic Things ecosystem. However, achieving safe autonomous navigation and high-level tasks such as exploration and surveillance with these tiny platforms is extremely challenging due to their limited resources. This work focuses on enabling the safe and autonomous flight of a pocket-size, 30-gram platform called Crazyflie 2.1 in a partially known environment. We propose a novel AIaided, vision-based reactive planning method for obstacle avoidance under the ambit of Integrated Sensing, Computing and Communication paradigm. We deal with the constraints of the nano-drone by splitting the navigation task into two parts: a deep learning-based object detector runs on the edge (external hardware) while the planning algorithm is executed onboard. The results show the ability to command the drone at 8 frames-per-second and a model performance reaching a COCO mean-average-precision of 60. 8 . Field experiments demonstrate the feasibility of the solution with the drone flying at a top speed of 1m/s while steering away from an obstacle placed in an unknown position and reaching the target destination. The outcome highlights the compatibility of the communication delay and the model performance with the requirements of the real-time navigation task. We provide a feasible alternative to a fully onboard implementation that can be extended to autonomous exploration with nano-drones. The Internet of Robotic Things (IoRT) is an emerging Internet of Things paradigm where robots are provided advanced situational awareness thanks to sensors and data analytics methods implemented onboard and on the edge [1].

These physical constraints cannot be fully addressed through advancements in control algorithms alone. Drawing inspiration from the winged flying squirrel, this paper proposes a highly maneuverable drone with agility-enhancing foldable wings. The additional air resistance generated by appropriately deploying these wings significantly improves the tracking performance of the proposed "flying squirrel" drone. By leveraging collaborative control between the conventional propeller system and the foldable wings--coordinated through the Thrust-Wing Coordination Control (TWCC) framework--the controllable acceleration set is expanded, allowing for the production of abrupt vertical forces unachievable with traditional wingless drones. The complex aerodynamics of the foldable wings are captured using a physics-assisted recurrent neural network (paRNN), which calibrates the angle of attack (AOA) to align with the real-world aerodynamic behavior of the wings. The model is trained on real-world flight data and incorporates flat-plate aerodynamic principles. Experimental results demonstrate that the proposed flying squirrel drone achieves a 13.1% improvement in tracking performance, as measured by root mean square error (RMSE), compared to a conventional wingless drone. A demonstration video is available on Y ouT ube: https://youtu.be/O8nrip18azY .

Pakistan's military says it brought down 25 Indian drones over cities including Karachi and Lahore. India says Pakistan had targeted India and Indian-administered Kashmir with drones and missiles that were shot down. The exchanges are fueling fears of a new phase in the ongoing tensions between the nuclear-armed neighbours.

The US military may soon have an army of faceless suicide bombers at their disposal, as an American defense contractor has revealed their newest war-fighting drone. AeroVironment unveiled the Red Dragon in a video on their YouTube page, the first in a new line of'one-way attack drones.' This new suicide drone can reach speeds up to 100 mph and can travel nearly 250 miles. The new drone takes just 10 minutes to set up and launch and weighs just 45 pounds. Once the small tripod the Red Dragon takes off from is set up, AeroVironment said soldiers would be able to launch up to five per minute.

The Israeli military has been altering commercial drones to carry bombs and surveil people in Gaza, an investigation by Al Jazeera's Sanad verification agency has found. According to Sanad, drones manufactured by the Chinese tech giant DJI have been used to attack hospitals and civilian shelters and to surveil Palestinian prisoners being forced to act as human shields for heavily armoured Israeli soldiers. This is not the first time DJI drones have been modified and used by armies. There were similar reports about both sides of the Russia-Ukraine war in 2022. At the time, DJI suspended all sales to both countries and introduced software modifications that restricted the areas where its drones could be used and how high they could fly.

Pakistan's military said on Thursday morning that the country's air defence system had brought down 25 Indian drones overnight over some of the country's chief cities, including Lahore and Karachi. At least one civilian has died, and five people were wounded, it said. India's Defence Ministry confirmed hours later that it had targeted Pakistan's air defence radars and claimed that it was able to "neutralize" one defence system in Lahore. It said Pakistan had attempted to attack India and Indian-administered Kashmir with drones and missiles overnight, but that these had been shot down. The drone attacks represent the latest escalation between the nuclear-armed neighbours, a day after India launched deadly missile strikes on Pakistan and Pakistan-administered Kashmir, killing at least 31 people, according to Islamabad.

Fox News senior foreign affairs correspondent Greg Palkot has the latest on the crisis on'Special Report.' India launched multiple Israeli-made Harop drones targeting Pakistan overnight and into Thursday, wounding at least four soldiers, Pakistan army officials said. Pakistani forces downed 25 of the drones, Pakistan army spokesperson Lt. Gen. Ahmad Sharif told The Associated Press. Debris from a downed drone that fell into the Sindh province killed one civilian and injured another. A drone damaged a military site near the city of Lahore, injuring four soldiers, and another went down in Rawalpindi, which is near the capital, Sharif said.

At least 39 Palestinians were killed in an Israeli strike and drone attack on a restaurant and market in Gaza.

Video shows drone debris in Lahore after Pakistan's army said it shot down 12 drones during an overnight Indian attack against several sites, killing one civilian and wounding four soldiers while targeting military positions.