All posts by Robotics News - Robot News, Robotics, Robots, Robotics Sciences

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Getting the right grip: Designing soft and sensitive robotic fingers

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.

Deep reinforcement-learning architecture combines pre-learned skills to create new sets of skills on the fly

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.

Robot vacuum cleaners can spy on private conversations

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.

Copying beetle wings to design MAVs that can recover from midair collisions

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.

RealAnt: A low-cost quadruped robot that can learn via reinforcement learning

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.

Robot hands one step closer to human thanks to AI algorithms

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.

Improved remote control of robots

Sometimes you need to get human knowledge and skills to places that are hazardous or difficult to access for people. The project entitled Predictive Avatar Control and Feedback (PACOF) is creating a robotic system that allows the robot operator to experience the location just as the robot does. Three researchers representing the three different disciplines of the University of Twente's EEMCS faculty are working together in this project.

Previewed Reality: A system that allows users to predict future changes in their environment

When robots and humans interact in a shared environment, it is important for them to move in ways that prevent collisions or accidents. To reduce the risk of collisions, roboticists have developed numerous of techniques that monitor an environment, predict the future actions of humans moving in it, identify safe trajectories for a robot and control its movements accordingly.
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