Combining two different kinds of signals could help engineers build prosthetic limbs that better reproduce natural movements, according to a new study. A combination of electromyography and force myography is more accurate at predicting hand movements than either method by itself.
An international team has explored how in future aerial robots could process construction materials precisely in the air -- an approach with great potential for difficult-to-access locations or work at great heights. The flying robots are not intended to replace existing systems on the ground, but rather to complement them in a targeted manner for repairs or in disaster areas, for instance.
New research can transform how hospitals triage, risk-stratify, and counsel patients to save lives.
Inspired by the movements of a tiny parasitic worm, engineers have created a 5-inch soft robot that can jump as high as a basketball hoop. Their device, a silicone rod with a carbon-fiber spine, can leap 10 feet high even though it doesn't have legs. The researchers made it after watching high-speed video of nematodes pinching themselves into odd shapes to fling themselves forward and backward.
After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists combine elements of different methods to improve algorithms or create new ones.
Most people generally are more concerned about the immediate risks of artificial intelligence than they are about a theoretical future in which AI threatens humanity. A new study reveals that respondents draw clear distinctions between abstract scenarios and specific tangible problems and particularly take the latter very seriously.
The invention is a metamaterial, which is a material engineered to feature new and unusual properties that depend on the material's physical structure rather than its chemical composition. In this case, the researchers built their metamaterial using a combination of simple plastics and custom-made magnetic composites. Using a magnetic field, the researchers changed the metamaterial's structure, causing it to expand, move and deform in different directions, all remotely without touching the metamaterial.
A recently created RoboBee is now outfitted with its most reliable landing gear to date, inspired by one of nature's most graceful landers: the crane fly. The team has given their flying robot a set of long, jointed legs that help ease its transition from air to ground. The robot has also received an updated controller that helps it decelerate on approach, resulting in a gentle plop-down.
Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers have now experimentally shown an all-optically controlled activation function based on traveling sound waves. It is suitable for a wide range of optical neural network approaches and allows operation in the so-called synthetic frequency dimension.
It's a game a lot of us played as children -- and maybe even later in life: unspooling measuring tape to see how far it would extend before bending. But to engineer, this game was an inspiration, suggesting that measuring tape could become a great material for a robotic gripper. The grippers would be a particularly good fit for agriculture applications, as their extremities are soft enough to grab fragile fruits and vegetables, researchers wrote. The devices are also low-cost and safe around humans.
A hopping, insect-sized robot can jump over gaps or obstacles, traverse rough, slippery, or slanted surfaces, and perform aerial acrobatic maneuvers, while using a fraction of the energy required for flying microbots.
Researchers from chemistry, biology, and medicine are increasingly turning to AI models to develop new hypotheses. However, it is often unclear on which basis the algorithms come to their conclusions and to what extent they can be generalized. A publicationnow warns of misunderstandings in handling artificial intelligence. At the same time, it highlights the conditions under which researchers can most likely have confidence in the models.
Do physicians or artificial intelligence (AI) offer better treatment recommendations for patients examined through a virtual urgent care setting? A new study shows physicians and AI models have distinct strengths. The study compared initial AI treatment recommendations to final recommendations of physicians who had access to the AI recommendations but may or may not have reviewed them.
How does a robotic arm or a prosthetic hand learn a complex task like grasping and rotating a ball? Researchers address the classic 'nature versus nurture' question. The research demonstrates that the sequence of learning, also known as the 'curriculum,' is critical for learning to occur. In fact, the researchers note that if the curriculum takes place in a particular sequence, a simulated robotic hand can learn to manipulate with incomplete or even absent tactile sensation.
When we move, it's harder for existing wearable devices to accurately track our heart activity. But researchers found that a starfish's five-arm shape helps solve this problem. Inspired by how a starfish flips itself over -- shrinking one of its arms and using the others in a coordinated motion to right itself -- scientists have created a starfish-shaped wearable device that tracks heart health in real time.