Disturbing footage emerged this week of a chess-playing robot breaking the finger of a seven-year-old child during a tournament in Russia.
What factors influence the embodiment felt towards parts of our bodies controlled by others? Using a new "joint avatar" whose left and right limbs are controlled by two people simultaneously, researchers have revealed that the visual information necessary to predict the partner's intentions behind limb movements can significantly enhance the sense of embodiment towards partner-controlled limbs during virtual co-embodiment. This finding may contribute to enhancing the sense of embodiment towards autonomous prosthetic limbs.
Researchers at Ulm University in Germany have recently developed a new framework that could help to make self-driving cars safer in urban and highly dynamic environments. This framework, presented in a paper pre-published on arXiv, is designed to identify potential threats around the vehicle in real-time.
A chess-playing robot grabbed the finger of its 7-year-old opponent and broke it during last week's Moscow Chess Open tournament, Russian media reported Monday.
Teams of mobile robots could be highly effective in helping humans to complete straining manual tasks, such as manufacturing processes or the transportation of heavy objects. In recent years, some of these robots have already been tested and introduced in real-world settings, attaining very promising results.
As the underwater robot OceanOneK carefully navigated toward the upper deck railing of the sunken Italian steamship Le Francesco Crispi about 500 m below the Mediterranean's surface this month (roughly a third of a mile), Stanford University roboticist Oussama Khatib felt as though he himself was there.
The robot watched as Shikhar Bahl opened the refrigerator door. It recorded his movements, the swing of the door, the location of the fridge and more, analyzing this data and readying itself to mimic what Bahl had done.
When communication lines are open, individual agents such as robots or drones can work together to collaborate and complete a task. But what if they aren't equipped with the right hardware or the signals are blocked, making communication impossible? University of Illinois Urbana-Champaign researchers started with this more difficult challenge. They developed a method to train multiple agents to work together using multi-agent reinforcement learning, a type of artificial intelligence.
Penn State agricultural engineers have developed, for the first time, a prototype "end-effector" capable of deftly removing unwanted apples from trees—the first step toward robotic, green-fruit thinning.
Researchers from Carnegie Mellon University took an all-terrain vehicle on wild rides through tall grass, loose gravel and mud to gather data about how the ATV interacted with a challenging off-road environment.
A newborn giraffe or foal must learn to walk on its legs as fast as possible to avoid predators. Animals are born with muscle coordination networks located in their spinal cord. However, learning the precise coordination of leg muscles and tendons takes some time. Initially, baby animals rely heavily on hard-wired spinal cord reflexes. While somewhat more basic, motor control reflexes help the animal to avoid falling and hurting themselves during their first walking attempts. The following, more advanced and precise muscle control must be practiced, until eventually the nervous system is well adapted to the young animal's leg muscles and tendons. No more uncontrolled stumbling—the young animal can now keep up with the adults.
Inflatable soft actuators that can change shape with a simple increase in pressure can be powerful, lightweight, and flexible components for soft robotic systems. But there's a problem: These actuators always deform in the same way upon pressurization.
The Tin Man didn't have one. The Grinch's was three sizes too small. And for soft robots, the electronically powered pumps that function as their "hearts" are so bulky and rigid, they must be decoupled from the robot's body—a separation that can leak energy and render the bots less efficient.
As every athletic or fashion-conscious person knows, our body image is not always accurate or realistic, but it's an important piece of information that determines how we function in the world. When you get dressed or play ball, your brain is constantly planning ahead so that you can move your body without bumping, tripping, or falling over.
EPFL researchers have used swarms of drones to measure city traffic with unprecedented accuracy and precision. Algorithms are then used to identify sources of traffic jams and recommend solutions to alleviate traffic problems.