Stéphane Fymat, the head of that new business, said Honeywell expects the hardware and software market for urban air taxis, drone cargo delivery, and other drone businesses to reach $120 billion by 2030 and Honeywell's market opportunity would be about 20% of that. He declined to say how much of that market Honeywell was targeting to capture, adding only that the unit has hundreds of employees with many engineers. Honeywell doesn't build drones itself but provides autonomous flight controls systems and aviation electronics. The new business creation comes as the coronavirus pandemic creates a surge of interest in drone deliveries; Fymat said it's accelerating the drone cargo delivery programs of some of its partners. Some of Honeywell's customers include Intel-backed Volocopter, Slovenia-based small aircraft maker Pipistrel, which is developing an electric vertical take-off and landing aircraft for cargo delivery, and UK-based Vertical Aerospace, which has test flown a prototype vehicle last year that can carry 250 kilograms and fly at 80 kilometers an hour.

Unmanned Aerial Vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas.

UAVs are tackling everything from disease control to vacuuming up ocean waste to delivering pizza, and more. Drone technology has been used by defense organizations and tech-savvy consumers for quite some time. However, the benefits of this technology extends well beyond just these sectors. With the rising accessibility of drones, many of the most dangerous and high-paying jobs within the commercial sector are ripe for displacement by drone technology. The use cases for safe, cost-effective solutions range from data collection to delivery. And as autonomy and collision-avoidance technologies improve, so too will drones' ability to perform increasingly complex tasks. According to forecasts, the emerging global market for business services using drones is valued at over $127B. As more companies look to capitalize on these commercial opportunities, investment into the drone space continues to grow. A drone or a UAV (unmanned aerial vehicle) typically refers to a pilotless aircraft that operates through a combination of technologies, including computer vision, artificial intelligence, object avoidance tech, and others. But drones can also be ground or sea vehicles that operate autonomously.

From advanced robotics in R&D labs to computer vision in warehouses, technology is making an impact on every step of the manufacturing process. Lights-out manufacturing refers to factories that operate autonomously and require no human presence. These robot-run settings often don't even require lighting, and can consist of several machines functioning in the dark. While this may sound futuristic, these types of factories have been a reality for more than 15 years. Famously, the Japanese robotics maker FANUC has been operating a "lights-out" factory since 2001, where robots are building other robots completely unsupervised for nearly a month at a time. "Not only is it lights-out," said FANUC VP Gary Zywiol, "we turn off the air conditioning and heat too." To imagine a world where robots do all the physical work, one simply needs to look at the most ambitious and technology-laden factories of today. For example, the Dongguan City, China-based phone part maker Changying Precision Technology Company has created an unmanned factory. Everything in the factory -- from machining equipment to unmanned transport trucks to warehouse equipment -- is operated by computer-controlled robots. The technical staff monitors activity of these machines through a central control system. Where it once required about 650 workers to keep the factory running, robot arms have cut Changying's human workforce to less than a tenth of that, down to just 60 workers. A general manager for the company said that it aims to reduce that number to 20 in the future. As industrial technology grows increasingly pervasive, this wave of automation and digitization is being labelled "Industry 4.0," as in the fourth industrial revolution. So, what does the future of factories hold? Manufacturers predict overall efficiency to grow annually over the next five years at 7x the rate of growth seen since 1990.

CLAVIER's central purpose is to find the most The use of composite materials, especially in aerospace applications, is on the increase because of their unique weight and strength qualities. Depending on the orientation of the graphite fibers, a part can be extremely flexible in one direction but rigid in another. In addition, a part made from composite material is both lighter and stronger than aluminum. The increased use of graphite parts, as well as the high cost of a spoiled part (as much as $50,000 for a single part), has put greater reliability and efficiency demands on a relatively new and complex manufacturing process. Composite part fabrication requires two major steps: layup and curing.

A common difficulty in diagnosing failures within Pratt & Whitney's F100-PW-100/200 gas turbine engine occurs when a fault in one part of a system--comprising an engine, an airframe, a test cell, and automated ground engine test set (AGETS) equipment--is manifested as an out-ofbound parameter elsewhere in the system. In such cases, the normal procedure is to run AGETS self-diagnostics on the abnormal parameter. However, because the self-diagnostics only test the specified local parameter, it will pass, leaving only the operators' experience and traditional fault-isolation manuals to locate the source of the problem in another part of the system. In such cases, the normal procedure is to run AGETS self-diagnostics on the abnormal parameter. However, because the self-diagnostics only test the parameter specified, it will pass because parameter tests are local tests that cannot uncover malfunctions in other parts of the system.

These are known as free-design parameters. When the range is finally obtained, the cycle begins again, based on perturbations of free-design parameters. Each program is "owned" and validated by a We have implemented a knowledge system that integrates the many computational programs (technology codes) Boeing aerospace vehicle designers use, thereby expediting design analysis. Because this system separates facts about attributes of the current set of technology codes from general knowledge about running the codes, those who maintain the system can keep it continuously up to date at low cost. The third approach left the technology codes untouched and built a procedural program that initiated separate, independent processes consisting of the technology codes communicating through a common database.

I'm in the cockpit of a Typhoon fighter jet. It's a scene inside an Oculus Rift headset at the new Training and Simulation Integration Facility belonging to defence company BAE Systems. It seems that to make the next great fighter jet, you start by working out what ideas you can pinch from the big consumer tech companies. The burning question on my mind, though, is how the company can even consider replacing cockpit controls with a view of the landscape.

If you've ever wondered about what it's like to be inside the International Space Station through the lens of, say, a drone, look no further. The Japan Aerospace Exploration Agency (JAXA) has released images and video from its JEM Internal Ball Camera, known as "Int-Ball," -- a camera drone that can record images and video while moving in space -- and the new footage gives us earth-dwellers a sneak peek of the happenings on the space laboratory. According to the JAXA, the Int-Ball was initially delivered to "Kibo," the Japanese Experiment Module on the International Space Station, on June 4, 2017, aboard SpaceX's uncrewed Dragon capsule. With the device and it's recording capabilities, JAXA is giving people a fascinating look at the inner-workings of the International Space Station.

Tesla and Space X chief executive Elon Musk has pushed again for the proactive regulation of artificial intelligence because "by the time we are reactive in AI regulation, it's too late". Because I think by the time we are reactive in AI regulation, it'll be too late," Musk told the meeting. "AI is a fundamental risk to the existence of human civilisation." While Musk has repeatedly shared his worries over AI and its development that is seen as inevitable in some regard, words appeared to hit home with multiple governors of the 32 taking part in the meeting, with follow-up questions looking for suggestions for how to go about regulating AI's development.