At least 12 people have been injured by shrapnel after Saudi air defences intercepted and destroyed a drone close to the kingdom's southern border with Yemen, according to state media. In comments carried by the Ekhbariya news channel, the Saudi Arabia-led military coalition battling Yemen's Houthi rebels said on Thursday travellers and workers of various nationalities had been injured by the falling debris in the vicinity of Abha international airport. Air traffic operations returned to normal after standard safety procedures were carried out, it added. There was no immediate claim of responsibility. Abha airport has often been a target of Houthi drone and missile attacks.

Those requirements could have played a part in the selection process for the Army's SRR program, as the service has previously had to halt the use of foreign-made drones. In 2017, the U.S. Army banned the use of all drones made by Chinese drone manufacturer DaJiang Innovations, or DJI, which supplies over half of all drones sold in the U.S. The company eventually created a U.S. government model in an attempt to allay these concerns. Still, in January 2021, the White House signed an Executive Order that instructed executive branch departments and agencies to examine all of their current drone technologies for potential threats and banned drones and drone subsystems from adversary countries defined as Iran, North Korea, Russia, and China. The Associated Press later reported in June 2021 that Pentagon had cleared some Chinese-made DJI drones for government use, but that report was quickly deemed inaccurate by the Department of Defense (DOD). "This report was inaccurate and uncoordinated, and its unauthorized release is currently under review by the department," the DOD said in a statement in response to the AP report.

This week, Verizon has announced 5G Ultra Wideband partnerships with a pair of US universities, aiming to use the network to help explore drone flight alongside the California Institute of Technology (Caltech) and Industry 4.0 advancements with Pennsylvania State University. At CAST, the operator said it would use the 5G deployment to explore how the low latency, high speeds, and massive capacity of 5G can be used to help reduce drones' need for in-built heavy computing hardware. Making use of edge computing, the AI systems the drone makes use of can function more efficiently, allowing for better real-time interpretation of data and near instantaneous in-flight adjustments. More specifically, the technology will be explored in the context of difficult weather conditions, with researchers hoping the new capabilities will allow drones to detect, interpret, and adjust to weather conditions in real-time. The CAST lab includes a three-story-tall aerodrome filled with adjustable fans, allowing the researchers to mimic weather conditions from a gentle breeze to gale-force winds; it can even be tilted 90 degrees to simulate vertical take-off under challenging conditions.

The Senate Judiciary committee holds a hearing on Wednesday on U.S. military drone strikes. The event is scheduled to begin at 10 a.m. This is a developing story and will be updated.

Human drone pilots have always been more efficient than their robotic counterparts -- until now. Researchers at the University of Zurich created an algorithm that finds the quickest path for a drone navigating a 3D racecourse in an indoor flight arena. The algorithm beat two professional drone pilots' times, according to a study published in Science Robotics this past July. And it can replicate that ideal route exactly, which is something humans can't do. There's still one way that we have the upper hand over machines, though: Humans can think on the fly, while the algorithm currently needs about an hour to calculate its trajectory.

Coco, a company that offers food deliveries by remote-controlled robot, has expanded beyond its home base of Los Angeles for the first time. The service is now available in Austin as it commences a nationwide rollout. Coco plans to bring its robots to Dallas, Houston and Miami in the next few months. The company says its service, which debuted in 2020, now has hundreds of delivery robots on the streets of LA, covering all of the city's major neighborhoods. Coco claims to reduce costs and deliver food to customers 30 percent faster than traditional methods with an on-time delivery rate of 97 percent.

We consider a setting where a team of humans oversee the coordination of multiple Unmanned Aerial Vehicles (UAVs) to perform a number of search tasks in dynamic environments that may cause the UAVs to drop out. Hence, we develop a set of multi-UAV supervisory control interfaces and a multi-agent coordination algorithm to support human decision making in this setting. To elucidate the resulting interactional issues, we compare manual and mixed-initiative task allocation in both static and dynamic environments in lab studies with 40 participants and observe that our mixed-initiative system results in lower workloads and better performance in re-planning tasks than one which only involves manual task allocation.

Observation planning for Unmanned Aerial Vehicles (UAVs) is a challenging task as it requires planning trajectories over a large continuous space and with motion models that can not be directly encoded into current planners. Furthermore, realistic problems often require complex objective functions that complicate problem decomposition. In this paper, we propose a local search approach to plan the trajectories of a fleet of UAVs on an observation mission. The strength of the approach lies in its loose coupling with domain specific requirements such as the UAV model or the objective function that are both used as black boxes. Furthermore, the Variable Neighborhood Search (VNS) procedure considered facilitates the adaptation of the algorithm to specific requirements through the addition of new neighborhoods. We demonstrate the feasibility and convenience of the method on a large joint observation task in which a fleet of fixed-wing UAVs maps wildfires over areas of a hundred square kilometers. The approach allows generating plans over tens of minutes for a handful of UAVs in matter of seconds, even when considering very short primitive maneuvers.

This paper presents an exploratory study where participants piloted a commercial UAS (unmanned aerial system) through an obstacle course. The goal was to determine how varying the instructions given to participants affected their performance. Preliminary data suggests future studies to perform, as well as guidelines for human-robot interaction, and some best practices for learning from demonstration studies.

What if a drone flight lands in your garden and delivers a product you booked online and takes off in seconds. Do you know how this happens? While many people are doubtful experts believe that the adoption of drones also known as unmanned aircraft systems (UAS), will become more common in the future. This blog will explain how AI drone services are transforming package industry. Drone delivery is employing unmanned aerial vehicles to deliver packages.