When we think of robots, we generally think of industrial robots in factories, putting hard labor to complete tasks that humans cannot. But robots are not just science fiction movies anymore. The humanoid robot Sophia is considered in such high regard that Saudi Arabia provided citizenship to her. Robots that are integrated with technologies like artificial intelligence, cybernetics, cognitive development, and neuroscience can perform multiple tasks at the same time, like plan, think, work, analyze, walk, and now, apparently fly. Researchers at the Italian Institute of Technology have recently been exploring the possibilities of creating a humanoid robot that can fly.

Researchers at the Italian Institute of Technology (IIT) have recently been exploring a fascinating idea, that of creating humanoid robots that can fly. To efficiently control the movements of flying robots, objects or vehicles, however, researchers require systems that can reliably estimate the intensity of the thrust produced by propellers, which allow them to move through the air. As thrust forces are difficult to measure directly, they are usually estimated based on data collected by onboard sensors. The team at IIT recently introduced a new framework that can estimate thrust intensities of flying multibody systems that are not equipped with thrust-measuring sensors. This framework, presented in a paper published in IEEE Robotics and Automation Letters, could ultimately help them to realize their envisioned flying humanoid robot.

The main goal of this post is to detail my development of a model for doing predictive maintenance on commercial turbofan engines. The predictive maintenance method utilized here is a data-driven method, which means that data from the operating jet engine is used to simulate predictive maintenance. The project's goal is to develop a prediction model for estimating a jet engine's Remaining Useful Life ( RUL) based on run-to-failure data from a fleet of comparable jet engines. The Prognostics and Health Management PHM08 Challenge Data Set was developed by NASA and is now available to the public. The data collection is used to forecast jet engine problems over time.

Jet engines can have up to 25,000 individual parts, making regular maintenance a tedious task that can take over a month per engine. Many components are located deep inside the engine and cannot be inspected without taking the machine apart, adding time and costs to maintenance. This problem is not only confined to jet engines, either; many complicated, expensive machines like construction equipment, generators, and scientific instruments require large investments of time and money to inspect and maintain. Researchers at Harvard University's Wyss Institute for Biologically Inspired Engineering and John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a micro-robot whose electroadhesive foot pads, origami ankle joints, and specially engineered walking gait allow it to climb on vertical and upside-down conductive surfaces, like the inside walls of a commercial jet engine. The work is reported in Science Robotics.

A robot with sticky feet that can climb up and down vertical walls as well as across the ceiling has been created by scientists. Harvard University engineers and Rolls-Royce partnered to make the robot which they say could inspect complex machines in the future. The device could be used in future to identify and maintain jet engines, scientific instruments and even generators. Jet engines can have up to 25,000 individual parts, making regular maintenance a tedious task that can take over a month per engine. Many components are located deep inside the engine and cannot be inspected without taking the machine apart, adding time and costs to maintenance.

I often find explanations of machine learning either too complex or overly simplistic. I've recently had some luck using a simple frame for explaining it to people in person. Let's see if I can quickly capture it in this post. Scratch the surface, and you see that machine learning is basically a kind of'statistical thinking.' We've long had tools for doing statistical analysis on data.

DELIVERING 25 PACKAGES by lorry or van might seem straightforward enough, but it is devilishly complex. The number of possible routes adds up to around 15 septillion (trillion trillion), according to Goldman Sachs, an investment bank. Integrating AI into the complex web of production and distribution--the supply chain--will have a bigger economic impact than any other application of the technology and affect a larger number of businesses, says Sudhir Jha of Infosys, a large IT company. McKinsey estimates that firms will derive between $1.3trn and $2trn a year in economic value from using AI in supply chains and manufacturing (see chart). Many firms are already using robots powered by machine learning to improve the running of their factories and warehouses.

Chinese scientists have developed a robot that could be straight out of the Iron Man movies. The two-legged bot is outfitted with small jet engines that are attached to its feet. Robotics engineers at Guangdong University of Tech's School of Automation in China strapped two duct fans to the robot's feet which allow it to cross wider distances than it would have been able to previously. Robotics engineers at Guangdong University of Tech's School of Automation in China developed a bipedal robot that can cross wide distances, thank to two small jet engines It also solves a major problem commonly experienced by robot developers. Most bipedal robots are only capable of making static movements like walking forward in short, controlled steps.

As you may have noticed, bipedal robots have a tendency to fall over. This often happens when the robots are trying to take a step, because stepping involves balancing on one foot while moving. All steps aren't equal, of course--you've got easy steps, when you're walking slowly across a flat surface, and you've got hard steps, when you're trying to avoid an obstacle by stepping over it or across it. Both robots and humans are constrained in the kinds of steps we're able to take by (among other things) how far we can stick a leg out without falling over. Humans mitigate this to some extent by dynamic walking, also known as constantly falling forward, but for less dynamic (quasi-static) robots, step length puts a significant limitation on the kinds of obstacles they can deal with.

So reads a New York Times headline on the biggest spectacle of the week. Elon Musk's latest rocket blasted into the atmosphere with David Bowie's iconic "Space Oddity" playing on auto-repeat, listened to by no one. Crowds cheered as the rocket roared upon takeoff--carrying a Tesla Roadster as payload, no less--and roared again as the boosters delivered themselves safely back to Earth. The sound of jet propulsion can be both mesmerizing and forgettable. On a recent trip to Washington, D.C., I became distinctly aware of a succession of rumbles in the sky early each morning: the steady sounds of the first banks of commercial airliners taking off from Reagan National Airport, across the Potomac. This is nothing out of the ordinary: just the groan of turbofans churning the outside air into propellant thrust so an airliner can ascend after takeoff.