Sunday, 2 June 2019

Stanford Doggo: a highly agile quadruped robot

Researchers at Stanford University have recently created an open-source quadruped robot called Stanford Doggo. Their robot, presented in a paper pre-published on arXiv and set to be published by IEEE Explore, exceeds the performance of many state-of-the-art legged robots in vertical jumping agility.

* This article was originally published here

Nicotine and caffeine withdrawal may lead to unnecessary suffering and testing in intensive care patients

Nicotine and caffeine withdrawal can cause unnecessary suffering to patients in intensive care units (ICUs), and could be leading to unneeded laboratory testing and diagnostic imaging such as X-rays and MRIs, according to a systematic review of clinical and observational studies involving 483 adults.

* This article was originally published here

Image: Hubble sees a galaxy bucking the trend

This luminous orb is the galaxy NGC 4621, better known as Messier 59. As this latter moniker indicates, the galaxy is listed in the famous catalog of deep-sky objects compiled by French comet-hunter Charles Messier in the 18th century. However, German astronomer Johann Gottfried Koehler is credited with discovering the galaxy just days before Messier added it to his collection in 1779.

* This article was originally published here

REPLAB: A low-cost benchmark platform for robotic learning

Researchers at UC Berkeley have developed a reproducible, low-cost and compact benchmark platform to evaluate robotic learning approaches, which they called REPLAB. Their recent study, presented in a paper pre-published on arXiv, was supported by Berkeley DeepDrive, the Office of Naval Research (ONR), Google, NVIDIA and Amazon.

* This article was originally published here

PULP Dronet: A 27-gram nano-UAV inspired by insects

Researchers at ETH Zürich and the University of Bologna have recently created PULP Dronet, a 27-gram nano-size unmanned aerial vehicle (UAV) with a deep learning-based visual navigation engine. Their mini-drone, presented in a paper pre-published on arXiv, can run aboard an end-to-end, closed-loop visual pipeline for autonomous navigation powered by a state-of-the-art deep learning algorithm.

* This article was originally published here