Why not give drone piloting a try? Now's a great time to do it since you can get the Ninja Dragons Blade X 4K Dual Camera Drone on sale for $120 off. As the name suggests, this quadcopter drone offers two cameras, a 1080p HD front camera and a 720p secondary camera to capture a broad view of the landscape and take photos and video from the sky. You can watch the camera feed in real time and control the drone with the included remote control or gesture controls. The remote has a 120-150 meter control distance while the electronic stabilization system ensures you always enjoy a stable flight.

Jeff Bezos likes to surprise. Roaming Amazon's global headquarters in 2013, the tycoon promised a television crew half his fortune if they could guess his company's latest innovation. "Oh my God," one of his wide-eyed guests exclaimed, as they caught sight of autonomous delivery drones. Bezos, a self-declared optimist, suggested it could happen by 2017, or maybe 2018. "I know this looks like science fiction. It's not," he told 60 Minutes on CBS in 2013.

Novice pilots find it difficult to operate and land unmanned aerial vehicles (UAVs), due to the complex UAV dynamics, challenges in depth perception, lack of expertise with the control interface and additional disturbances from the ground effect. Therefore we propose a shared autonomy approach to assist pilots in safely landing a UAV under conditions where depth perception is difficult and safe landing zones are limited. Our approach comprises of two modules: a perception module that encodes information onto a compressed latent representation using two RGB-D cameras and a policy module that is trained with the reinforcement learning algorithm TD3 to discern the pilot's intent and to provide control inputs that augment the user's input to safely land the UAV. The policy module is trained in simulation using a population of simulated users. Simulated users are sampled from a parametric model with four parameters, which model a pilot's tendency to conform to the assistant, proficiency, aggressiveness and speed. We conduct a user study (n = 28) where human participants were tasked with landing a physical UAV on one of several platforms under challenging viewing conditions. The assistant, trained with only simulated user data, improved task success rate from 51.4% to 98.2% despite being unaware of the human participants' goal or the structure of the environment a priori. With the proposed assistant, regardless of prior piloting experience, participants performed with a proficiency greater than the most experienced unassisted participants.

A U.S. Navy warship in the northern Red Sea on Thursday shot down three cruise missiles and several drones launched from Yemen that the Pentagon said might have been headed toward Israel. "We cannot say for certain what these missiles and drones were targeting, but they were launched from Yemen heading north along the Red Sea, potentially towards targets in Israel," Brig. Gen. Patrick Ryder, the Pentagon spokesman, told reporters. The missiles and drones were launched by pro-Iranian Houthi rebels in Yemen amid a flurry of drone attacks against American troops in Iraq and Syria over the past three days, General Ryder said. The incidents underscored the risks that the conflict between Israel and the Palestinian group Hamas could spiral into a wider war.

Teams of flying robots can be used for inspection, delivery, and construction tasks, in which they might be required to fly very close to each other. In such close-proximity cases, nonlinear aerodynamic effects can cause catastrophic crashes, necessitating each robots' awareness of the surrounding. Existing approaches rely on multiple, expensive or heavy perception sensors. Such perception methods are impractical to use on nano multirotors that are constrained with respect to weight, computation, and price. Instead, we propose to use the often ignored yaw degree-of-freedom of multirotors to spin a single, cheap and lightweight monocular camera at a high angular rate for omnidirectional awareness of the neighboring robots. We provide a dataset collected with real-world physical flights as well as with 3D-rendered scenes and compare two existing learning-based methods in different settings with respect to success rate, relative position estimation, and downwash prediction accuracy. We demonstrate that our proposed spinning camera is capable of predicting the presence of aerodynamic downwash with an $F_1$ score of over 80% in a challenging swapping task.

Perception is necessary for autonomous navigation in an unknown area crowded with obstacles. It's challenging for a robot to navigate safely without any sensors that can sense the environment, resulting in a $\textit{blind}$ robot, and becomes more difficult when comes to a group of robots. However, it could be costly to equip all robots with expensive perception or SLAM systems. In this paper, we propose a novel system named $\textbf{ColAG}$, to solve the problem of autonomous navigation for a group of $\textit{blind}$ UGVs by introducing cooperation with one UAV, which is the only robot that has full perception capabilities in the group. The UAV uses SLAM for its odometry and mapping while sharing this information with UGVs via limited relative pose estimation. The UGVs plan their trajectories in the received map and predict possible failures caused by the uncertainty of its wheel odometry and unknown risky areas. The UAV dynamically schedules waypoints to prevent UGVs from collisions, formulated as a Vehicle Routing Problem with Time Windows to optimize the UAV's trajectories and minimize time when UGVs have to wait to guarantee safety. We validate our system through extensive simulation with up to 7 UGVs and real-world experiments with 3 UGVs.

A miniature robotic blimp, as one type of lighter-than-air aerial vehicle, has attracted increasing attention in the science and engineering field for its long flight duration and safe aerial locomotion. While a variety of miniature robotic blimps have been developed over the past decade, most of them utilize the buoyant lift and neglect the aerodynamic lift in their design, thus leading to a mediocre aerodynamic performance. This letter proposes a new design of miniature robotic blimp that combines desirable features of both a robotic blimp and a fixed-wing glider, named the Robotic Gliding Blimp, or RGBlimp. This robot, equipped with an envelope filled with helium and a pair of wings, uses an internal moving mass and a pair of propellers for its locomotion control. This letter presents the design, dynamic modeling, prototyping, and system identification of the RGBlimp. To the best of the authors' knowledge, this is the first effort to systematically design and develop such a miniature robotic blimp with hybrid lifts and moving mass control. Experimental results are presented to validate the design and the dynamic model of the RGBlimp. Analysis of the RGBlimp aerodynamics is conducted which confirms the performance improvement of the proposed RGBlimp in aerodynamic efficiency and flight stability.

Drone expert Brett Velicovich joined'FOX & Friends First' to discuss attacks against U.S. military bases in the Middle East as war rages between Israel and Hamas. A drone strike targeted a U.S. base in Syria on Wednesday, the same day as the attempted drone attacks in Iraq, Fox News has learned. A U.S. defense official told Fox News that an undisclosed number of drones targeted the U.S. Al-Tanf base, located near Syria's shared border with Iraq and Jordan. Lebanon's Iran-aligned Al Mayadeen TV reported on Thursday that two U.S. military bases in Syria came under attack, Reuters reported. In addition to the drone attack on the Al-Tanf base, Al Mayadeen TV reported a missile targeted the Conoco base in the countryside of the northern Deir al-Zor region.

We haven't heard much on the state of Amazon's drone deliveries, but the company still seems focused on exploring the possibilities. A report earlier this year said Amazon had made only a handful of deliveries due to FAA regulations. However, in the announcement of prescription deliveries in parts of Texas, Amazon said its drones "have safely delivered hundreds of household items in College Station [in Texas] since December 2022." Customers at College Station are now eligible for aerial deliveries of "more than 500 medications" for common conditions like the flu, asthma and pneumonia. Texas has established itself as a hotbed for drone delivery trials.

Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics and AI, with numerous applications in real-world scenarios. One such scenario is filming scenes with multiple actors, where the goal is to capture the scene from multiple angles simultaneously. Here, we present a formation-based filming directive of task assignment followed by a Conflict-Based MAPF algorithm for efficient path planning of multiple agents to achieve filming objectives while avoiding collisions. We propose an extension to the standard MAPF formulation to accommodate actor-specific requirements and constraints. Our approach incorporates Conflict-Based Search, a widely used heuristic search technique for solving MAPF problems. We demonstrate the effectiveness of our approach through experiments on various MAPF scenarios in a simulated environment. The proposed algorithm enables the efficient online task assignment of formation-based filming to capture dynamic scenes, making it suitable for various filming and coverage applications.