'Dragon eggs' lowered into the heart of volcanoes using drones could help monitor for clues of future eruptions with more precision, scientists have revealed. Such extreme, hazardous and unpredictable environments present a very difficult challenge to reliably record volcanic behaviour. For some volcanoes, it is simply too dangerous for humans to get close enough to take readings manually. However, scientists have got around this problem by creating highly sensitive pods that can be positioned in dangerous locations to provide real-time data on eruptions. Dubbed'dragon eggs', scientists say these devices could also monitor other natural phenomenon such as glaciers, geological faults and man-made hazards such as nuclear waste storage sites.
Lockheed Martin is launching AlphaPilot, an open innovation challenge focused on artificial intelligence for autonomous systems. Your challenge is to design an artificial intelligence and machine learning (AI/ML) framework capable of flying a drone through several professional drone racing courses without human intervention or navigational pre-programing. By participating in this competition, your knowledge and ideas can contribute directly toward the future of autonomous transportation, delivery, disaster relief, and even space exploration! Lockheed Martin is launching AlphaPilot to address the role of autonomy in our collective futures. Through a fun and challenging objective, AlphaPilot will unite a diverse community of practice and emerging experts around the common challenges of trusted autonomous systems.
Drones could soon be flown by autonomous AI pilots if Lockheed Martin has any say. The aerospace giant is partnering with the Drone Racing League to pit humans and AI against one another to see which can navigate a drone through a high-flying course the fastest. Called the AlphaPilot Innovation Challenge, teams must craft AI system based around Nvidia's Jetson deep learning technology and fly the drone without any pre-programming or human intervention. Lockheed Martin is partnering with ESPN's Drone Racing League to pit humans and AI against one another to see which can navigate a drone through a high-flying course the fastest The first team that can outrun a human DRL pilot wins a $250,000 reward, while the grand prize winner can claim up to $1 million. The winning AI system could spell the future of autonomous drone operations, according to Lockheed Martin.
Many real-world objects are designed by smooth curves, especially in the domain of aerospace and ship, where aerodynamic shapes (e.g., airfoils) and hydrodynamic shapes (e.g., hulls) are designed. To facilitate the design process of those objects, we propose a deep learning based generative model that can synthesize smooth curves. The model maps a low-dimensional latent representation to a sequence of discrete points sampled from a rational B\'ezier curve. We demonstrate the performance of our method in completing both synthetic and real-world generative tasks. Results show that our method can generate diverse and realistic curves, while preserving consistent shape variation in the latent space, which is favorable for latent space design optimization or design space exploration.
Machine vision, or computer vision, is a popular research topic in artificial intelligence (AI) that has been around for many years. However, machine vision still remains as one of the biggest challenges in AI. In this article, we will explore the use of deep neural networks to address some of the fundamental challenges of computer vision. In particular, we will be looking at applications such as network compression, fine-grained image classification, captioning, texture synthesis, image search, and object tracking. Even though deep neural networks feature incredible performance, their demands for computing power and storage pose a significant challenge to their deployment in actual application.
Alexander Gerst will test the technology demonstrator aboard the ISS Watson AI (IBM's artificial intelligence technology) is designed to support space flight crews Friedrichshafen / Bremen, 26/02/2018 – Airbus, in cooperation with IBM, is developing CIMON (Crew Interactive MObile CompanioN), an AI-based assistant for astronauts for the DLR Space Administration. The technology demonstrator, which is the size of a medicine ball and weighs around 5 kg, will be tested on the ISS by Alexander Gerst during the European Space Agency's Horizons mission between June and October 2018. "In short, CIMON will be the first AI-based mission and flight assistance system," said Manfred Jaumann, Head of Microgravity Payloads from Airbus. "We are the first company in Europe to carry a free flyer, a kind of flying brain, to the ISS and to develop artificial intelligence for the crew on board the space station." Pioneering work was also being done in the area of manufacturing, Jaumann continued, with the entire structure of CIMON, which is made up of plastic and metal, created using 3D printing.
Elon Musk's SpaceX program plans to break another important barrier in private space flight Tuesday with the re-launch of a previously-used Block 5 booster just three months after its initial flight. In conjunction with the re-launch, SpaceX announced plans to shorten re-launch times for the Block 5 booster to less than 24 hours by 2019, which would further solidify SpaceX's dominance of the private space flight market? Private space flight companies have been involved in a technological arms race for years on a number of different fronts. One of the most important fronts is the development of an inexpensive reusable rocket booster system that can be used to launch satelites and manned craft into space.
Engineers at Caltech have developed a new control algorithm that enables a single drone to herd an entire flock of birds away from the airspace of an airport. The work is described in "Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle," published in the IEEE Transactions on Robotics. The project was inspired by the 2009 "Miracle on the Hudson," when US Airways Flight 1549 struck a flock of geese shortly after takeoff and pilots Chesley Sullenberger and Jeffrey Skiles were forced to land in the Hudson River off Manhattan. "The passengers on Flight 1549 were only saved because the pilots were so skilled," says Soon-Jo Chung, an associate professor of aerospace and Bren Scholar in the Division of Engineering and Applied Science as well as a JPL research scientist, and the principal investigator on the drone herding project. "It made me think that next time might not have such a happy ending.