EPFL spin-off Aica has developed AI-based software that makes industrial robots easier to program and more capable of adapting. The software is designed in a modular format so that operators can build a customized application based on their needs. Aica's advancement expands the range of tasks that robots can perform while cutting implementation costs.
For decades, the attitude of unions and their advocates to increased automation could be summed up in one word: no. They feared that every time a machine was slipped into the workflow, a laborer lost a job.
Scientists often look to nature for cues when designing robots—some robots mimic human hands while others simulate the actions of octopus arms or inchworms. Now, researchers in the University of Georgia College of Engineering have designed a new soft robotic gripper that draws inspiration from an unusual source: pole beans.
Jeffrey C. Trinkle has always had a keen interest in robot hands. And, though it may be a long way off, Trinkle, who has studied robotics for more than thirty years, says he's most compelled by the prospect of robots performing "dexterous manipulation" at the level of a human "or beyond."
Researchers at Tecnologico de Monterrey in Mexico have recently created a low-cost robotic arm that could enhance online robotics education, allowing teachers to remotely demonstrate theoretical concepts explained during their lessons. This robotic arm, presented in a paper published in Hardware X, is fully open source and can be easily assembled by all teachers and educators worldwide.
New research has shown robots can encourage humans to take greater risks in a simulated gambling scenario than they would if there was nothing to influence their behaviours. Increasing our understanding of whether robots can affect risk-taking could have clear ethical, practical and policy implications, which this study set out to explore.
Japan's SoftBank Group will sell an 80 percent stake in robotics firm Boston Dynamics to Hyundai, the trio said Friday, in a deal that values the US company at $1.1 billion.
Although robotics has reshaped and even redefined many industrial sectors, there still exists a gap between machines and humans in fields such as health and elderly care. For robots to safely manipulate or interact with fragile objects and living organisms, new strategies to enhance their perception while making their parts softer are needed. In fact, building a safe and dexterous robotic gripper with human-like capabilities is currently one of the most important goals in robotics.
A team of researchers from the University of Edinburgh and Zhejiang University has developed a way to combine deep neural networks (DNNs) to create a new type of system with a new kind of learning ability. The group describes their new architecture and its performance in the journal Science Robotics.
Northwestern University researchers have developed a first-of-its-kind life-like material that acts as a soft robot. It can walk at human speed, pick up and transport cargo to a new location, climb up hills and even break-dance to release a particle.
When your robot vacuum cleaner does its work around the house, beware that it could pick up private conversations along with the dust and dirt. Computer scientists from NUS have demonstrated that it is indeed possible to spy on private conversations using a common robot vacuum cleaner and its built-in Light Detection and Ranging (Lidar) sensor.
When danger approaches, the Moroccan flic-flac spider takes the shape of a ball and rolls away to safety. Just as the trick of shape-shifting to one's environment has proved invaluable for many creatures, Yale researchers say it could be equally useful for robots.
A pair of researchers at Konkuk University has designed a miniaturized micro air vehicle (MAV) capable of recovering from midair collisions. In their paper published in the journal Science, Hoang Vu Phan and Hoon Cheol Park describe their study of collision recovery in rhinoceros beetles and how they applied their findings to the design of a new kind of MAV.
Over the past decade or so, roboticists and computer scientists have tried to use reinforcement learning (RL) approaches to train robots to efficiently navigate their environment and complete a variety of basic tasks. Building affordable robots that can support and manage the exploratory controls associated with RL algorithms, however, has so far proved to be fairly challenging.
The Shadow Robot Dexterous Hand is a robot hand, with size, shape and movement capabilities similar to those of a human hand. To give the robotic hand the ability to learn how to manipulate objects researchers from WMG, University of Warwick, have developed new AI algorithms.