We are announcing the release of our state-of-the-art off-policy model-free reinforcement learning algorithm, soft actor-critic (SAC). This algorithm has been developed jointly at UC Berkeley and Google, and we have been using it internally for our robotics experiment.
The world is full of life-threatening jobs. There was a time when humans merely gritted their teeth, accepted the risk and trusted that the training they received would protect them from harm. However, there is a growing trend of using robots to do the tasks that could harm humans.
Vehicles increasingly contain electronic systems that assist drivers with monitoring, warning, braking, and steering tasks. Semiconductor companies are innovating to increase safety, while reducing weight, size, and complexity.
This comprehensive article dives deep into the world of robotics, exploring the history, types, engineering components, applications, and future trends of robots, offering readers an in-depth understanding of how these remarkable machines work and shape our lives.
The hospitality industry can leverage the gender characteristics of service robots to influence customers' decisions, according to new research from a team in the Penn State School of Hospitality Management.
Service robots have evolved from simple automated machines to intelligent adaptive systems that can navigate unpredictable environments and interact with humans.
From hospital wards to crop fields, from microscopic swarms to biohybrid machines powered by fungi, robotics research at Cornell spans an astonishing range of scale, application and ambition.
An AI control system co-developed by SMART researchers enables soft robotic arms to learn a broad set of motions once and adapt instantly to changing conditions without retraining.
A new glove with more than three dozen actuators across all five fingers and the palm, developed by Cornell researchers, aims to reduce swelling for people suffering from edema.
AI-powered artificial muscles made from pliable materials are reshaping recovery, from stroke rehabilitation to prosthetic design. These machines help people regain motion, strength, and confidence.
We are announcing the release of our state-of-the-art off-policy model-free reinforcement learning algorithm, soft actor-critic (SAC). This algorithm has been developed jointly at UC Berkeley and Google, and we have been using it internally for our robotics experiment.
The world is full of life-threatening jobs. There was a time when humans merely gritted their teeth, accepted the risk and trusted that the training they received would protect them from harm. However, there is a growing trend of using robots to do the tasks that could harm humans.
Vehicles increasingly contain electronic systems that assist drivers with monitoring, warning, braking, and steering tasks. Semiconductor companies are innovating to increase safety, while reducing weight, size, and complexity.
New insights about how euglena navigate their world could lead to advances in the way miniature robots of the future maneuver through the bloodstream or other watery environments.
Daniel Lofaro talks about how he works hard to make things easier and how co-robotics are the way forward, and how bringing cost down cost and better AI is critical for this.
Like its predecessor, JackRabbot 2 is learning how to navigate safely through spaces occupied by people, following the rules of human etiquette. What it learns could help it move comfortably among us in the future.
Meet Tribot, the three-legged origami robot designed and built by EPFL scientists. Tri- for three legs and -bot for robot, this super-light critter fits in the palm of your hand, is cheap to build, runs on less than one watt of power, and may one day be deployed in mass for search and rescue mission
Autonomous driving is no longer sci-fi, it’s become a reality and soon to be hitting our streets. Every week, Autotech companies are announcing their plan for self-driving tech. But, no two autonomous driving technologies are exactly alike.