New Method Developed to Improve Robot Performance in Helping Patients

Robots are becoming an increasingly important part of human care. (AFP)
Robots are becoming an increasingly important part of human care. (AFP)
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New Method Developed to Improve Robot Performance in Helping Patients

Robots are becoming an increasingly important part of human care. (AFP)
Robots are becoming an increasingly important part of human care. (AFP)

Robots are becoming an increasingly important part of human care, according to researchers based in Japan. To help improve the safety and efficacy of robotic care, the scientists have developed a control method that could help them better replicate human movement when lifting and moving a patient.

“In recent years, shortage of caregivers has become a serious social problem as the result of a falling birth rate and an aging population,” said researcher Changan Jiang, assistant professor of mechanical engineering at Ritsumeikan University, according to the German news agency.

According to the Phys.org website, the researchers have developed a method to control the movement of a nursing care robot's arm that doesn't produce the harmful movements or frictions usually produced by traditional robots' arms.

"Instead of compensating the friction, the new arm utilizes static friction that could reduce the patients' suffering when moved on their beds", the website reported.

In a related context, a team of researchers at the University of South California has developed a new technique that teaches robots different skills by competing with humans.

"This is the first robot learning effort using adversarial human users," said Stefanos Nikolaidis, a computer science researcher.

"Picture it like playing a sport: if you're playing tennis with someone who always lets you win, you won't get better. Same with robots: If we want them to learn a manipulation task, such as grasping, so they can help people, we need to challenge them," he added.

In his experiment, Nikolaidis used reinforcement learning, a technique in which artificial intelligence programs "learn" from repeated experimentation.

During the study, the researchers found that involving a human factor in teaching the AI system could help the robot acquire further skills by watching a human being completing his task. The experiment went something like this: the robot attempts to grasp an object, while the human observes the simulated robot's grasp. If the grasp is successful, the human tries to snatch the object from the robot's grasp.



Explorer: Sonar Image Was Rock Formation, Not Amelia Earhart Plane

A statue of Amelia Earhart at the US Capitol. Nathan Howard / GETTY IMAGES/AFP
A statue of Amelia Earhart at the US Capitol. Nathan Howard / GETTY IMAGES/AFP
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Explorer: Sonar Image Was Rock Formation, Not Amelia Earhart Plane

A statue of Amelia Earhart at the US Capitol. Nathan Howard / GETTY IMAGES/AFP
A statue of Amelia Earhart at the US Capitol. Nathan Howard / GETTY IMAGES/AFP

A sonar image suspected of showing the remains of the plane of Amelia Earhart, the famed American aviatrix who disappeared over the Pacific in 1937, has turned out to be a rock formation.

Deep Sea Vision (DSV), a South Carolina-based firm, released the blurry image in January captured by an unmanned submersible of what it said may be Earhart's plane on the seafloor.

Not so, the company said in an update on Instagram this month, AFP reported.

"After 11 months the waiting has finally ended and unfortunately our target was not Amelia's Electra 10E (just a natural rock formation)," Deep Sea Vision said.

"As we speak DSV continues to search," it said. "The plot thickens with still no evidence of her disappearance ever found."

The image was taken by DSV during an extensive search in an area of the Pacific to the west of Earhart's planned destination, remote Howland Island.

Earhart went missing while on a pioneering round-the-world flight with navigator Fred Noonan.

Her disappearance is one of the most tantalizing mysteries in aviation lore, fascinating historians for decades and spawning books, movies and theories galore.

The prevailing belief is that Earhart, 39, and Noonan, 44, ran out of fuel and ditched their twin-engine Lockheed Electra in the Pacific near Howland Island while on one of the final legs of their epic journey.

Earhart, who won fame in 1932 as the first woman to fly solo across the Atlantic, took off on May 20, 1937 from Oakland, California, hoping to become the first woman to fly around the world.

She and Noonan vanished on July 2, 1937 after taking off from Lae, Papua New Guinea, on a challenging 2,500-mile (4,000-kilometer) flight to refuel on Howland Island, a speck of a US territory between Australia and Hawaii.

They never made it.