Until now, when scientists created magnetic robots, their magnetization profiles were generally fixed, enabling only a specific type of shape programming capability using applied external magnetic fields. Researchers at the Max Planck Institute for Intelligent Systems (MPI-IS) have now proposed a new magnetization reprogramming method that can drastically expand the complexity and diversity of the shape-programming capabilities of such robots.
People who care informally for sick or disabled friends and relatives often become invisible in their own lives. Focusing on the needs of those they care for, they rarely get the chance to talk about their own emotions or challenges, and this can lead to them feeling increasingly stressed and isolated.
For 20 hours a day, seven days a week, a security robot rolls around the old Kansas City Star building on the 1600 block of McGee Street, like the 21st century version of a street patrolling beat cop.
Growing up, we learn to push just hard enough to move a box and to avoid touching a hot pan with our bare hands. Now, a robot hand has been developed that also has these instincts.
Social companion robots are no longer just science fiction. In classrooms, libraries and homes, these small machines are designed to read stories, play games or offer comfort to children. They promise to support learning and companionship, yet their role in family life often extends beyond their original purpose.
Researchers from the Istituto Italiano di Tecnologia (IIT) in Genoa (Italy) and Brown University in Providence (U.S.) have discovered that people sense the hand of a humanoid robot as part of their body schema, particularly when it comes to carrying out a task together, like slicing a bar of soap.
Exoskeletons typically work by implementing motions programmed in advance and having the user call for them, making it difficult to use them for a wide range of motions in real-life environments.
Birds flock in order to forage and move more efficiently. Fish school to avoid predators. And bees swarm to reproduce. Recent advances in artificial intelligence have sought to mimic these natural behaviors as a way to potentially improve search-and-rescue operations or to identify areas of wildfire spread over vast areas—largely through coordinated drone or robotic movements. However, developing a means to control and utilize this type of AI—or "swarm intelligence"—has proved challenging.
A team of scientists from China and the U.S. is pioneering the development of bubble-powered robots, which could one day replace needles for painless drug delivery into the body. Inspired by nature, the researchers developed a new technique that harnesses the energy released by a collapsing bubble in a liquid, a process known as cavitation.
A spinal cord injury in most vertebrates likely inhibits locomotion and induces paralysis—not so in eels. They not only possess the ability to move through water, and surprisingly, across land when intact, but can also continue to swim even if their spinal cord is severed.
Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of robotic arms to work together faster and smarter in busy industrial settings, potentially saving manufacturers hundreds of hours of planning time and unlocking new levels of flexibility and efficiency.
General Motors Co. worker Annie Ignaczak spent years walking in circles on concrete factory floors, assembling the same parts and counting down hundreds of pieces she and her coworkers needed to finish before lunch.
For all their technological brilliance, from navigating distant planets to performing complex surgery, robots still struggle with a few basic human tasks. One of the most significant challenges is dexterity, which refers to the ability to grasp, hold and manipulate objects. Until now, that is. Scientists from the Toyota Research Institute in Massachusetts have trained a robot to use its entire body to handle large objects, much like humans do.
In everyday life, it's a no-brainer to be able to grab a cup of coffee from the table. Multiple sensory inputs such as sight (seeing how far away the cup is) and touch are combined in real-time. However, recreating this in artificial intelligence (AI) is not quite as easy.
Researchers at the University of Minnesota Twin Cities have developed aerial robots equipped with artificial intelligence (AI) to detect, track and analyze wildfire smoke plumes. This innovation could lead to more accurate computer models that will improve air quality predictions for a wide range of pollutants.