IEEE Robotics & Automation Society Italian Chapter (I-RAS)

Sidewinders' bellies are studded with tiny pits and have few, if any, of the tiny spikes found on the bellies of other snakes. The discovery includes a mathematical model linking these distinct structures to function.

Researchers have discovered how to make materials that snap and reset themselves, only relying upon energy flow from their environment. The discovery may prove useful for various industries that want to source movement sustainably, from toys to robotics, and is expected to further inform our understanding of how the natural world fuels some types of movement.

Researchers have been using artificial intelligence (AI) to develop a mobile device that can identify certain patients at risk of sudden cardiac death.

Researchers developed a neural network that learns on the job, not just during training. The 'liquid' network varies its equations' parameters, enhancing its ability to analyze time series data. The advance could boost autonomous driving, medical diagnosis, and more.

Researchers have developed an automated way to design customized hardware that speeds up a robot's operation. The system, called robomorphic computing, accounts for the robot's physical layout in suggesting an optimized hardware architecture.

Robots are widely used to build cars, paint airplanes and sew clothing in factories, but the assembly of microscopic components, such as those for biomedical applications, has not yet been automated. Lasers could be the solution. Now, researchers have used lasers to create miniature robots from bubbles that lift, drop and manipulate small pieces into interconnected structures.

Computer scientists developed a deep learning method to create realistic objects for virtual environments that can be used to train robots. The researchers used TACC's Maverick2 supercomputer to train the generative adversarial network. The network is the first that can produce colored point clouds with fine details at multiple resolutions.

Researchers present an optical flow-based learning process that allows robots to estimate distances through the visual appearance (shape, color, texture) of the objects in view. This artificial intelligence (AI)-based learning strategy increases the navigation skills of small flying drones and entails a new hypothesis on insect intelligence.

Scientists are combining artificial intelligence and advanced computer technology with biological know how to identify insects with supernatural speed. This opens up new possibilities for describing unknown species and for tracking the life of insects across space and time.

Computer-based artificial intelligence can function more like human intelligence when programmed to use a much faster technique for learning new objects, say two neuroscientists who designed such a model that was designed to mirror human visual learning.

An international team of researchers, including Professor Roberto Morandotti of the Institut national de la recherche scientifique (INRS), just introduced a new photonic processor that could revolutionize artificial intelligence, as reported by the prestigious journal Nature.

We are fascinated by machines that can control cars, compose symphonies, or defeat people at chess, Go, or Jeopardy! While more progress is being made all the time in Artificial Intelligence (AI), some scientists and philosophers warn of the dangers of an uncontrollable superintelligent AI. Using theoretical calculations, an international team of researchers shows that it would likely not be possible to control a superintelligent AI.

Like a longtime couple who can predict each other's every move, a new robot has learned to predict its partner robot's future actions and goals based on just a few initial video frames. The study is part of a broader effort to endow robots with the ability to understand and anticipate the goals of other robots, purely from visual observations.

A Swinburne-led team has demonstrated the world's fastest and most powerful optical neuromorphic processor for artificial intelligence. The neuromorphic processor operates faster than 10 trillion operations per second and is capable of processing ultra-large scale data.

Drones, robots and autonomous systems can transform the natural world in and around cities for people and wildlife.

Scientists have developed a machine-learning method that crunches massive amounts of data to help determine which existing medications could improve outcomes in diseases for which they are not prescribed.

Researchers have proposed a new principle by which active matter systems can spontaneously order, without need for higher level instructions or even programmed interaction among the agents. And they have demonstrated this principle in a variety of systems, including groups of periodically shape-changing robots called 'smarticles.'

A new study by neuroscientists demonstrates that the brain does not remap itself even with long-term bionic limb use, posing challenges for the development of realistic prosthetic limbs.

A new device developed by engineers can recognize hand gestures based on electrical signals detected in the forearm. The system, which couples wearable biosensors with artificial intelligence (AI), could one day be used to control prosthetics or to interact with almost any type of electronic device.

Researchers have successfully developed technology to simulate phenomena for which the detailed mechanism or formula are unexplained. They did this by using AI to create a model, which is faithful to the laws of physics, from observational data. This technology will hopefully enable these kinds of phenomena (e.g. wave motion and fracture mechanics) to be more accurately predicted by computer simulations.