Orbital missions will unlock the next phase of Starship's development, providing better data on the performance of the spacecraft's heat shield and allowing for tests of in-orbit refueling, which will be essential for missions to Mars. Save this storyIt has been two weeks since SpaceX's last Starship test flight, and engineers have diagnosed issues with its heat shield, identified improvements, and developed a preliminary plan for the next time the ship heads into space. Bill Gerstenmaier, a SpaceX executive in charge of build and flight reliability, presented the findings Monday at the American Astronautical Society's Glenn Space Technology Symposium in Cleveland. The rocket lifted off on August 26 from SpaceX's launch pad in Starbase, Texas, just north of the US-Mexico border. It was the 10th full-scale test flight of SpaceX's Super Heavy booster and Starship upper stage, combining to form the world's largest rocket. There were a couple of overarching objectives on the August 26 test flight.

Science Space Solar System Moons NASA's next trip around the moon could have your name on it'Fly my name to the moon, let me play among the stars.' Breakthroughs, discoveries, and DIY tips sent every weekday. As NASA gears up next year's Artemis II test flight, you have an opportunity to add your name to the spacecraft's digital manifest. You can claim your "spot" and boarding pass alongside the crew by adding your name here by January 21, 2026. You can also add your name and get a boarding pass in Spanish .

A solar-powered surveillance drone with a wingspan larger than a Boeing 747 jumbo jet could fly for weeks or months at a time, according to its operator, while watching for drug-smuggling vessels, pirates or naval warships. It has been performing test flights off the US Gulf Coast this month. The Skydweller drone, operated by US-Spanish firm Skydweller Aero, has a wingspan of 72 metres – exceeding the width of most commercial passenger jets. But it weighs only about 2500 kilograms – as much as a Ford F-150 truck. It is based on the Solar Impulse 2 aircraft, which performed the first solar-powered flight around the world in 2016. Skydweller Aero purchased and converted the pioneering aircraft with the goal of building a fleet of similar solar-powered, carbon-fibre drones capable of "perpetual flight" at altitudes exceeding 13 kilometres in daytime hours.

MOMAV (Marco's Omnidirectional Micro Aerial Vehicle) is a multirotor drone that is fully actuated, meaning it can control its orientation independently of its position. MOMAV is also highly symmetrical, making its flight efficiency largely unaffected by its current orientation. These characteristics are achieved by a novel drone design where six rotor arms align with the vertices of an octahedron, and where each arm can actively rotate along its long axis. Various standout features of MOMAV are presented: The high flight efficiency compared to arm configuration of other fully-actuated drones, the design of an original rotating arm assembly featuring slip-rings used to enable continuous arm rotation, and a novel control allocation algorithm based on sequential quadratic programming (SQP) used to calculate throttle and arm-angle setpoints in flight. Flight tests have shown that MOMAV is able to achieve remarkably low mean position/orientation errors of 6.6mm, 2.1° (σ: 3.0mm, 1.0°) when sweeping position setpoints, and 11.8mm, 3.3° (σ: 8.6mm, 2.0°) when sweeping orientation setpoints.

Drones are increasingly used in forestry to capture high-resolution remote sensing data. While operations above the forest canopy are already highly automated, flying inside forests remains challenging, primarily relying on manual piloting. Inside dense forests, reliance on the Global Navigation Satellite System (GNSS) for localization is not feasible. Additionally, the drone must autonomously adjust its flight path to avoid collisions. Recently, advancements in robotics have enabled autonomous drone flights in GNSS-denied obstacle-rich areas. In this article, a step towards autonomous forest data collection is taken by building a prototype of a robotic under-canopy drone utilizing state-of-the-art open-source methods and validating its performance for data collection inside forests. The autonomous flight capability was evaluated through multiple test flights in two boreal forest test sites. The tree parameter estimation capability was studied by conducting diameter at breast height (DBH) estimation using onboard stereo camera data and photogrammetric methods. The prototype conducted flights in selected challenging forest environments, and the experiments showed excellent performance in forest reconstruction with a miniaturized stereoscopic photogrammetric system. The stem detection algorithm managed to identify 79.31 % of the stems. The DBH estimation had a root mean square error (RMSE) of 3.33 cm (12.79 %) and a bias of 1.01 cm (3.87 %) across all trees. For trees with a DBH less than 30 cm, the RMSE was 1.16 cm (5.74 %), and the bias was 0.13 cm (0.64 %). When considering the overall performance in terms of DBH accuracy, autonomy, and forest complexity, the proposed approach was superior compared to methods proposed in the scientific literature. Results provided valuable insights into autonomous forest reconstruction using drones, and several further development topics were proposed.

From Harry Potter to The Jetsons, flying cars have been staple features of science fiction blockbusters for years. But with these futuristic vehicles rapidly getting closer to becoming a reality, a key question remains – where will they operate? In the hopes of making air travel simpler, Skyports Infrastructure has revealed plans to build the UK's first permanent'vertiport'. The vertiport will be built in Bicester, Oxfordshire, starting this autumn and will serve as a base for electric air taxis. Duncan Walker, chief executive of Skyports, said: 'The tests and trials we conduct at this facility will be instrumental to the future of quiet, electric, vertical flight.'

The space travel company SpaceX has completed its most successful test yet of Starship, the world's most powerful rocket -- but as the unmanned rocket completed its flight, it was destroyed upon re-entry into Earth's atmosphere. Thursday's test flight was the third conducted with Starship rockets, ahead of planned missions with the United States space agency NASA to send astronauts to the moon. SpaceX, a company founded and owned by tech entrepreneur Elon Musk, livestreamed the latest Starship experiment, noting that the vessel flew farther and faster than it had in two previous tests. However, as the rocket returned to Earth, it lost communication with SpaceX engineers. The livestream suddenly cut off, its final image showing the rocket's heat shield flaring with friction.

Reinforcement learning is of increasing importance in the field of robot control and simulation plays a~key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatably avoid trees and fly through the forest.

On the morning of December 1, 2022, a modified F-16 fighter jet codenamed VISTA X-62A took off from Edwards Air Force Base, roughly 60 miles north of Los Angeles. Over the course of a short test flight, the VISTA engaged in advanced fighter maneuver drills, including simulated aerial dogfights, before landing successfully back at base. While this may sound like business as usual for the US's premier pilot training school--or like scenes lifted straight from Top Gun: Maverick--it was not a fighter pilot at the controls but, for the first time on a tactical aircraft, a sophisticated AI. Overseen by the US Department of Defense, VISTA X-62A undertook 12 AI-led test flights between December 1 and 16, totaling more than 17 hours of autonomous flight time. The breakthrough comes as part of a drive by the United States Air Force Vanguard to develop unmanned combat aerial vehicles.

A modified F-16 fighter jet has successfully flown and fought another aircraft while being entirely controlled by artificial intelligence (AI). During test flights, the jet, known as'X-62A' or'VISTA', performed takeoffs, landings and combat manoeuvres without human intervention for a total of over 17 hours. They took place in December 2022 at the Edwards Air Force Base in California, USA, and showed that it is possible to completely hand over the reigns to AI in battle. The algorithms which powered it were developed by the Defense Advanced Research Projects Agency (DARPA) - the research branch of the US Department of Defense. This marks the first time AI has been used on a tactical aircraft as, prior to this milestone, it had only been used in computer simulations of F-16 dogfights.