Today, Alphabet's X moonshot division (formerly known as Google X) unveiled the Everyday Robot project , whose goal is to develop a "general-purpose learning robot." The idea is that its robots could use cameras and complex machine learning algorithms to see and learn from the world around them without needing to be coded for every individual movement.
The team is testing robots that can help out in workplace environments, though right now, these early robots are focused on learning how to sort trash. Here's what one of them looks like — it reminds me of a very tall, one-armed Wall-E (ironic, given what the robots are tasked to do):
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China hotel has a cheery robot to deliver your coffee pods - The Washington Post
The goal, analysts say, was to boost automation and give the sleeping giant a global manufacturing edge for years to come. Chinese factories are being flooded with robots, but now the machines are appearing in more public settings as well.
This week, Anna Fifield, The Washington Post's Beijing bureau chief , found this out firsthand during a reporting trip to Shanghai. While checking into a local hotel, she said, she noticed a slender trash-can-shaped robot in the lobby, its cylindrical body plastered with a tiny human-ish face. The hotel's receptionist told Fifield that if she needed anything, she could request a robot delivery.
Researchers Develop Soft Skin-Like Pocket-Sized Robots - Robotics Business Review
Discovering a new way of embedding artificial muscles and electrical adhesion into soft materials, researchers at the University of Bristol have created stretchable, skin-like robots that can be rolled up and placed in a pocket. The advance could lead to the creation of new thin and light robots for environmental monitoring, deployment in hazardous environments, robot grippers for delicate objects, and new wearable technologies.
A paper on the technology, titled "All-Soft Skin-Like Structures for Robotic Locomotion and Transportation," was recently published in Soft Robotics (the journal, not the company). While traditional robots are rigid and incompliant, softer robots are compliant and can stretch and twist to adapt to their environments. But until this discovery, researchers said, soft robots have separated their movement abilities from their capabilities to grip the surface they move on.
Why Robots Should Learn to Build Crappy Ikea Furniture | WIRED
It's become a veritable rite of passage for humans settling into their first apartments: Assemble a piece of Ikea furniture from a cryptic set of pictures without having either you, or the item in question, fall apart.
For you and me, assembling Ikea furniture is simultaneously simple and hellish: You lament the process, but your great big brain can (mostly) translate the abstract instructions into something real. You run into all kinds of problems, but your creativity surmounts them with ease; the Allen wrench cramps your hand, but your human powers of manipulation are unparalleled.
Quite a lot has been going on:
Scientists help soldiers figure out what robots know -- ScienceDaily
An Army-led research team developed new algorithms and filled in knowledge gaps about how robots contribute to teams and what robots know about their environment and teammates.
Dr. Kristin Schaefer-Lay, an engineer with the U.S. Army Combat Capabilities Development Command's Army Research Laboratory, is part of a multidisciplinary team of reseachers from the Army, Carnegie Mellon University, University of Minnesota and the University of Central Florida -- amongst others, who developed specific algorithms and novel artificial intelligence approaches to support the development of a shared context between team members through effective bidirectional communication.
Here's where robots are replacing workers fastest - Futurity
Workers assemble Ford vehicles at the Chicago Assembly Plant on June 24, 2019 in Chicago, Illinois. (Credit: Scott Olson/Getty Images )
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Robots are displacing younger, less-educated, and minority workers in the Midwest manufacturing industry at the highest rates, a new report shows.
However, the findings also show that a strong economic recovery over the past decade has saved many jobs and slowed automation in the United States.
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