Neuromorphic computing entails building architectures inspired by elements of the human brain, such as neural organization and synapses. These architectures have proved to be highly promising and advantageous for a number of applications, as they can have both memory...
In recent years, many research teams worldwide have been developing and evaluating techniques to enable different locomotion styles in legged robots. One way of training robots to walk like humans or animals is by having them analyze and emulate real-world...
Robots that are made of flexible materials that can be inflated have a number of desirable properties, including their light weight and high levels of compliance (i.e. the ability to undergo elastic deformation). These qualities make them ideal for completing tasks in...
Scientific texts, such as research articles or reviews, can sometimes be difficult to analyze and understand, particularly for non-expert readers. In recent years, engineers have thus tried to develop approaches that can automatically extract the most important...
Researchers at Konkuk University in South Korea recently created KUBeetle-S, a flying robot inspired by a species of horned beetle called Allomyrina dichotomy, which is among the largest insects on the planet. Allomyrina dichotomy weighs approximately 5 to 10 g and...
Edge computing is an innovative computing method that can enhance the efficiency of machine learning and other computational techniques by running fewer processes in the cloud and distributing the processing load across nearby edge devices (i.e., edge nodes). This...
In recent years, researchers have developed increasingly advanced natural language processing (NLP) techniques that can be trained to process, interpret and respond to sentences in human languages. In addition, some have developed toolkits that can guide researchers...
Researchers at Toshiba Corporate R&D Center and Kioxia Corporation in Japan have recently carried out a study exploring the feasibility of using nonlinear ferroelectric tunnel junction (FTJ) memristors to perform low-power linear computations. Their paper,...
Researchers at the University of Bristol have recently trained a deep-neural-network-based model to gather tactile information about 3-D objects. In their paper, published in IEEE Robotics & Automation Magazine, they applied the deep learning technique to a...
The ability to estimate the physical properties of objects is of key importance for robots, as it allows them to interact more effectively with their surrounding environment. In recent years, many robotics researchers have been specifically trying to develop...