Walking and running is notoriously difficult to recreate in robots. Now, a group of researchers has overcome some of these challenges by creating an innovative method that employs central pattern generators -- neural circuits located in the spinal cord that generate rhythmic patterns of muscle activity -- with deep reinforcement learning. The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from walking to running, and allows for adapting to environments with unstable surfaces.
Emergency departments nationwide are overcrowded and overtaxed, but a new study suggests artificial intelligence (AI) could one day help prioritize which patients need treatment most urgently.
Researchers have harnessed the technology behind foundation models, which power tools like ChatGPT, to discover new cancer imaging biomarkers that could transform how patterns are identified from radiological images. Improved identification of such patterns can greatly impact the early detection and treatment of cancer.
Engineers created a catapillar-shaped robot that splits into segments and reassembles, hauls cargo, and crawls through twisting courses.
A stretchy electronic skin could equip robots and other devices with the same softness and touch sensitivity as human skin, opening up new possibilities to perform tasks that require a great deal of precision and control of force.
Researchers have successfully leveraged robotic assistance in the manufacture of wind turbine blades, allowing for the elimination of difficult working conditions for humans and the potential to improve the consistency of the product.
New algorithm encourages robots to move more randomly to collect more diverse data for learning. In tests, robots started with no knowledge and then learned and correctly performed tasks within a single attempt. New model could improve safety and practicality of self-driving cars, delivery drones and more.
A four-legged robot trained with machine learning has learned to avoid falls by spontaneously switching between walking, trotting, and pronking -- a milestone for roboticists as well as biologists interested in animal locomotion.
Researchers have constructed a robot that uses machine learning to fully automate a complicated microinjection process used in genetic research.
The use of pliable soft materials to collaborate with humans and work in disaster areashas drawn much recent attention. However, controlling soft dynamics for practical applications has remained a significant challenge. Researchers developed a method to control pneumatic artificial muscles, which are soft robotic actuators. Rich dynamics of these drive components can be exploited as a computational resource.
Researchers have developed tiny, flexible devices that can wrap around individual nerve fibers without damaging them. The researchers combined flexible electronics and soft robotics techniques to develop the devices, which could be used for the diagnosis and treatment of a range of disorders, including epilepsy and chronic pain, or the control of prosthetic limbs.
Robotics engineers have worked for decades and invested many millions of research dollars in attempts to create a robot that can walk or run as well as an animal. And yet, it remains the case that many animals are capable of feats that would be impossible for robots that exist today.
An ongoing research aims to create adaptable safety systems for highly automated off-road mobile machinery to meet industry needs. Research has revealed critical gaps in compliance with legislation related to public safety when using mobile working machines controlled by artificial intelligence.
The study highlights the rapid progress and transformative potential of AI in weather prediction.
A new robotic suction cup which can grasp rough, curved and heavy stone, has been developed by scientists.