Manipulation


Iran tests new missile after U.S. criticizes arms program

The Japan Times

The United States has imposed unilateral sanctions on Iran, saying its missile tests violate a U.N. resolution, which calls on Tehran not to undertake activities related to missiles capable of delivering nuclear weapons. "You are seeing images of the successful test of the Khoramshahr ballistic missile with a range of 2,000 km, the latest missile of our country," state television said, adding this was Iran's third missile with such a range. "Extremely concerned by reports of Iran missile test, which is inconsistent with U.N. resolution 2231. Iran's defense minister said on Saturday foreign pressures would not affect Iran's missile program.


Girl with 3D-printed robotic hand to throw first pitch at World Series game

ZDNet

A seven-year-old Las Vegas girl will throw out the first pitch in game four of the upcoming World Series. Hailey Dawson was born with Poland syndrome and is missing three fingers on her right hand. At the time, Dawson couldn't find any companies that could fit Hailey with a robotic hand for a reasonable cost. Over more than a year, the UNLV engineering students and faculty worked to develop a variety of robotic 3-D printed hands for then-five-year-old Hailey.


Artificial skin lets robot hand feel hot or cold

USATODAY

A robot hand with artificial skin reaches for a glass of ice water. Researchers at the University of Houston have created an artificial skin that allows a robotic hand to sense the difference between heat and cold. The discovery of stretchable electronics could have a significant impact in the wearables market, with devices such as health monitors or biomedical devices, says Cunjiang Yu, an assistant professor of mechanical engineering at the University of Houston and the lead author for the paper. When the stretchable electronic skin was applied to a robotic hand, it could tell the difference between hot and cold water.


Girl with robotic hand will throw out first pitch during World Series

Los Angeles Times

Hailey Dawson is 7 years old and has already thrown out the first pitch before many Major League Baseball games. By using a robotic hand made with a 3-D printer, she has thrown out the ceremonial first pitch for several MLB teams, including the Washington Nationals, Baltimore Orioles, New York Mets, Milwaukee Brewers, Seattle Mariners, Oakland A's, Minnesota Twins and Detroit Tigers. The Las Vegas native first threw out a ceremonial pitch before a UNLV game in 2014, then set her sights on doing so at major league stadiums. More than 20 of the league's teams, including the Dodgers and Angels, reached out to Dawson through that tweet.


Self healing skin brings Terminator robots one step closer

Daily Mail

Now experts have created a synthetic skin that aims to mimic nature's self-repairing abilities, allowing robots to recover from'wounds' sustained while undertaking their duties. Now experts have created a synthetic skin (pictured on robotic hand) that aims to mimic nature's self-repairing abilities To create their synthetic flesh, the scientists used jelly-like polymers that melt into each together when heated and then cooled. Their flexibility allows them to be used for a wide variety of applications, from grabbing delicate and soft objects in the food industry to performing minimally invasive surgery. The flexibility of these soft robots allows them to be used for a wide variety of applications, from grabbing delicate and soft objects in the food industry (pictured) to performing minimally invasive surgery.


South Korea: No Proof Cash to Kaesong Went to North Korea Arms Programs

U.S. News

SEOUL (Reuters) - There was no evidence that North Korea had diverted wages paid to its workers by South Korean companies operating in now-suspended industrial park on their border to its weapons programs, a South Korean official said on Thursday.


A lizard-inspired robot gripper may solve our space-junk problems

Engadget

But engineers at Stanford may have made a breakthrough: They've designed a robotic gripper based on gecko's feet that works in zero-g. The problem with existing technology is that everything is designed to work at Earth's gravity, within Earth's temperature range. Geckos can climb up walls and other vertical surfaces because of microscopic flaps on their feet that create an adhesive force. By modeling their technology on these flaps, the team was able to create a gripper that only requires a small push to stick to a surface.


uni.news: Self-Learning Robot Hands

#artificialintelligence

Thomas Schack's research group, for instance, investigated which characteristics study participants perceived to be significant in grasping actions. In one study, test subjects had to compare the similarity of more than 100 objects. In another study, test subjects' eyes were covered and they had to handle cubes that differed in weight, shape, and size. From one of the monitors, Flobi follows the movements of the hands and reacts to the researchers' instructions.


Self Learning AI Robot Hands

#artificialintelligence

Researchers at Bielefeld University have developed a grasping learning system based on robotic hands. The system called "Famula" works without knowing the specific characteristics of objects such as pieces of fruit or tools in advance. "Our system learns by trying out and exploring by itself – in the same way that babies approach new objects", says Prof. Dr. Helge Ritter. The grasping learning system was developed as part of the "Famula" large-scale project at Bielefeld University's Cluster of Excellence Cognitive Interaction Technology (CITEC).


An AI Robot Learned How to Pick up Objects After Training Only in the Virtual World

#artificialintelligence

To address this issue, researchers at the University of California, Berkeley, trained a deep learning system on a cloud-based data set of more than a thousand objects, exposing it to each one's 3D shape and appearance, as well of the physics of grasping it. Afterward, they tested their system using physical objects that weren't included in its digital training set. They plan to publicly release their data set, which should help others create their own dexterous robots and perhaps even inspire a few innovators to think of other ways to use the virtual world for training AI systems. "It's hard to collect large data sets of robotic data," Stefanie Tellex, an assistant professor specializing in robot learning at Brown University, explained to MIT Technology Review.