Whether you're reaching for a mug, a pencil or someone's hand, you don't need to consciously instruct each of your fingers on where they need to go to get a proper grip.
Over the past decades, roboticists have introduced a wide range of advanced systems that can move around in their surroundings and complete various tasks. Most of these robots can effectively collect images and other data in their surroundings, using computer vision algorithms to interpret it and plan their future actions.
Generative AI and robotics are moving us ever closer to the day when we can ask for an object and have it created within a few minutes. In fact, MIT researchers have developed a speech-to-reality system, an AI-driven workflow that allows them to provide input to a robotic arm and "speak objects into existence," creating things like furniture in as little as five minutes.
Researchers at the University of Maryland, Baltimore County (UMBC) have extracted the building blocks of precise hand gestures used in the classical Indian dance form Bharatanatyam—and found a richer "alphabet" of movement compared to natural grasps. The work could improve how we teach hand movements to robots and offer humans better tools for physical therapy.
Underwater octopuses change their body color and texture in the blink of an eye to blend perfectly into their surroundings when evading predators or capturing prey. They transform their bodies to match the colors of nearby corals or seaweed, turning blue or red, and move by softly curling their arms or snatching prey.
EPFL scientists have integrated discarded crustacean shells into robotic devices, leveraging the strength and flexibility of natural materials for robotic applications.
In the future, tiny flying robots could be deployed to aid in the search for survivors trapped beneath the rubble after a devastating earthquake. Like real insects, these robots could flit through tight spaces larger robots can't reach, while simultaneously dodging stationary obstacles and pieces of falling rubble.
Imagine having a continuum soft robotic arm bend around a bunch of grapes or broccoli, adjusting its grip in real time as it lifts the object. Unlike traditional rigid robots that generally aim to avoid contact with the environment as much as possible and stay far away from humans for safety reasons, this arm senses subtle forces, stretching and flexing in ways that mimic more of the compliance of a human hand. Its every motion is calculated to avoid excessive force while achieving the task efficiently.
Embodied artificial intelligence (AI) systems are robotic agents that rely on machine learning algorithms to sense their surroundings, plan their actions and execute them. A key aspect of these systems are visual perception modules, which allow them to analyze images captured by cameras and interpret them.
A research team at Kumamoto University (Japan) has unveiled a new mathematical framework that makes it possible to accurately model systems using multiple sensors that operate at different sensing rates. This breakthrough could pave the way for safer autonomous vehicles, smarter robots, and more reliable sensor networks.
Our muscles are nature's actuators. The sinewy tissue is what generates the forces that make our bodies move. In recent years, engineers have used real muscle tissue to actuate "biohybrid robots" made from both living tissue and synthetic parts. By pairing lab-grown muscles with synthetic skeletons, researchers are engineering a menagerie of muscle-powered crawlers, walkers, swimmers, and grippers.
When it comes to training robots to perform agile, single-task motor skills, such as handstands or backflips, artificial intelligence methods can be very useful. But if you want to train your robot to perform multiple tasks—say, performing a backward flip into a handstand—things get a little more complicated.
Large language models (LLMs), such as the model underpinning the functioning of OpenAI's platform ChatGPT, are now widely used to tackle a wide range of tasks, ranging from sourcing information to the generation of texts in different languages and even code. Many scientists and engineers also started using these models to conduct research or advance other technologies.
More than 150 Chinese companies are making humanoid robots but a market bubble risks forming in the rapidly growing futuristic industry, a Beijing official has warned.
Robotic systems that mirror humans both in their appearance and movements, also known as humanoid robots, could be best suited for tackling many tasks that are currently performed by human agents. These include household chores, such as cleaning, tidying up and cooking, as well as the transport of items or the assembly of products.