A team of researchers at Carnegie Mellon University believe they have developed the first AI pilot that enables autonomous aircraft to navigate a crowded airspace. The artificial intelligence can safely avoid collisions, predict the intent of other aircraft, track aircraft and coordinate with their actions, and communicate over the radio with pilots and air traffic controllers. The researchers aim to develop the AI so the behaviors of their system will be indistinguishable from those of a human pilot. "We believe we could eventually pass the Turing Test," said Jean Oh, an associate research professor at CMU's Robotics Institute (RI) and a member of the AI pilot team, referring to the test of an AI's ability to exhibit intelligent behavior equivalent to a human. To interact with other aircraft as a human pilot would, the AI uses both vision and natural language to communicate its intent with other aircraft, whether piloted or not.

If autonomous drones and flying taxis are going to thrive, they'll need AI that can handle a wide range of conditions -- and Microsoft thinks it can help build that AI. The company has unveiled a Project AirSim platform that helps manufacturers create, train and test the algorithms guiding autonomous aircraft. The Azure-based technology has virtual vehicles fly millions of flights through detailed simulations in a matter of seconds, gauging their ability to handle different obstacles and weather conditions. A drone maker can quickly find out if their machine will avoid birds, or use too much battery power countering strong winds. Developers can use trained AI "building blocks" to get started, so they won't need vast amounts of technical know-how.

Researchers are working on an interdisciplinary research project funded by NASA that aims to design and develop a safety management system for electric autonomous aircraft. Assistant professor in the Department of Mechanical and Aerospace Engineering, researches control, optimization, machine learning and Artificial Intelligence (AI) in air transportation and aviation. His lab builds flight deck and ground-based automation and decision support tools to improve and ensure safety for emerging aircraft types and flight operations. While a lot of the innovation in Artificial Intelligence and machine learning applications has been focused on revolutionizing the internet and digital connectivity, group of researchers are focused on expanding those benefits into transforming air transportation for physical connectivity and future mobility. Researchers are investigating on a new three-year, $2.5 million NASA System-Wide Safety grant project.

A George Washington University School of Engineering and Applied Science professor is working on an interdisciplinary research project funded by NASA that aims to design and develop a safety management system for electric autonomous aircraft. Peng Wei, an assistant professor in the Department of Mechanical and Aerospace Engineering, researches control, optimization, machine learning and artificial intelligence (AI) in air transportation and aviation. His lab builds flight deck and ground-based automation and decision support tools to improve and ensure safety for emerging aircraft types and flight operations. While a lot of the innovation in AI and machine learning applications has been focused on revolutionizing the internet and digital connectivity, Dr. Wei is part of a group of researchers focused on expanding those benefits into transforming air transportation for physical connectivity and future mobility. Dr. Wei is the principal investigator of a new three-year, $2.5 million NASA System-Wide Safety grant project.

FedEx Corp. is looking at using small self-flying cargo planes to serve remote areas after experimenting with a technology startup on autonomous aircraft, said Chief Executive Officer Fred Smith. The effort builds on the courier's work with Silicon Valley's Reliable Robotics, which was founded by veterans of Elon Musk's Space Exploration Technologies Corp. With approval from the U.S. Federal Aviation Administration, Reliable Robotics demonstrated in June a fully automated remote landing of a Cessna 208 Caravan turboprop owned by FedEx. "This initiative deals with small turboprop airplanes and in this particular case the single-engine C208, which we're looking at putting in very remote and uninhabited areas as part of our network," Smith said Monday at FedEx's annual shareholder meeting. FedEx pilots shouldn't be concerned about robots stealing their jobs -- for now.

The aviation industry is the front-runner of autonomous vehicles. It has long beat the automotive sector in the race of autonomy. People feel comfortable with the implication of self-driving vehicles when they grow fond of the concept of autonomy. The self-flying planes are already on use with the help of flight plan created by pilots. For example, if a pilot takes off the seat-belt sign, there are chances that the flight is being self-driven.

We often hear about autonomous vehicles and self-driving cars, but you would be surprised how close the aviation industry is to complete this transition. The thing is that aviation has an emerging need for a solution because tourism is booming, more people than ever are traveling around the world, yet there's the scarcity of pilots. In 2017, there were 609 thousand certified pilots, which seems a lot, but the number drastically declined from 827 thousand in 1980. And the number of qualified pilots is gradually decreasing. One way to tackle the problem is to accelerate an autonomous aircraft development. Even though the idea might sound intimidating at best, it's not that far from happening.

Boeing Co said on Thursday it invested in Near Earth Autonomy, a Pittsburgh-based firm that develops technologies enabling autonomous flight such as drones. In addition to the undisclosed investment, Boeing said the two companies will also explore products and applications for emerging markets such as urban mobility. It was the first investment in autonomous technologies by Boeing's venture capital arm, Boeing HorizonX, since it was established in April of this year, Boeing said. Near Earth Autonomy, a spin-off from the Carnegie Mellon University's Robotics Institute, develops technologies including sensor suites, three dimensional mapping and survey, and collision detection and avoidance that enables aircraft to operate autonomously. Near Earth Autonomy, a spin-off from the Carnegie Mellon University's Robotics Institute, develops technologies including sensor suites, three dimensional mapping and survey, and collision detection and avoidance that enables aircraft to operate autonomously. Just some of the firm's core technologies include: Sensor suites: Near Earth sensor packages perceive the world in 3D, enabling mapping and surveying for piloted and autonomous aircraft.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. If you haven't seen this blooper reel of rocket mishaps from SpaceX, it's spectacular: I love this because it's a reminder that robotics (and space robotics especially) is very very hard, and part of the normal process of discovery and learning is trying things and having them go wrong. What should be a normal part of that process is also sharing the failures on video to help the rest of us feel better about our own projects, so especially if you're doing research, make sure and keep a copy of all of those outtakes, and send them to us! We wrote about Fable when we first saw it at IROS 2014 in Chicago, and a few years later, they've shipped hundreds of robots to customers in Denmark and are now starting to ship to the rest of the world.

Abstract: "Teams of robots often have to assign target locations among themselves and then plan collision-free paths to their target locations. Examples include autonomous aircraft towing vehicles and automated warehouse systems. Today, hundreds of robots already navigate autonomously in Amazon fulfillment centers to move inventory pods all the way from their storage locations to the packing stations. Path planning for these robots can be NP-hard, yet one must find high-quality collision-free paths for them in real-time. The shorter these paths are, the fewer robots are needed and the cheaper it is to open new fulfillment centers.