Posts Tagged ‘robot’

screen_shot_2018-09-06_at_154717_1024

by LINDSAY DODGSON

Medical training exercises are getting more and more realistic. Recently, companies have developed robots that medical students can practise on.

The idea is that these pretend people can lead us a little way into the uncanny valley, so we have to deal with the emotional response as well as the methodology behind a procedure.

One of the latest medical robots is called HAL. It takes the form of a five-year-old boy which can respond to certain questions, follow a finger with its eyes, bleed, and convulse.

It even has a pulse.

HAL was built by Gaumard Scientific, a company that produced the first synthetic human skeleton for medical schools.

The company’s technology has come a long way since then, having developed a synthetic boy who can simulate many medical problems, cry tears, and shout for its mother.

Using HAL is supposed to help students retain their knowledge better, because it is as close to treating a real person without actually using a human volunteer.

HAL’s other functions include going into cardiac arrest, anaphylactic shock, and the ability to have its blood sugar, blood oxygen level, and carbon dioxide levels measured.

Also, its pupils dilate when a light is shined into its eyes.

In a promotional video, a doctor asks HAL about how much its head hurts, and it responds “an eight”.

To prepare for the really bad injuries and problems, HAL can be hooked up to real hospital machines and shocked with a defibrillator.

When it’s awake it can be set to several different emotional states, including lethargic, angry, amazed, quizzical, and anxious.

The idea is to make HAL just realistic enough to help students with their studies, but not so realistic that it’s too traumatic to deal with when they have to slit its throat to insert a trachael tube.

HAL is one of a few medical robots currently in use. On the Gaumard website there is also a premature baby simulator, and a scarily realistic robot that gives birth.

These pretend people are very different from the lifeless dummies medical professionals have used for decades.

“I’ve seen several nurses be like, ‘Whoa it moves!'” Marc Berg, the medical director at the Revive Initiative for Resuscitation Excellence at Stanford, told Wired in a chilling article.

“I think that’s kind of similar to the idea that if you’ve driven a car for 20 years and then you got a brand new car, you’re kind of amazed initially.”

Watch the video explaining all of HAL’s functions here:

https://www.sciencealert.com/this-robot-child-bleeds-screams-and-cries-for-its-mother

Advertisements

Robots, take note: When working in tight, crowded spaces, fire ants know how to avoid too many cooks in the kitchen.

Observations of fire ants digging an underground nest reveal that a few industrious ants do most of the work while others dawdle. Computer simulations confirm that, while this strategy may not be the fairest, it is the most efficient because it helps reduce overcrowding in tunnels that would gum up the works. Following fire ants’ example could help robot squads work together more efficiently, researchers report in the Aug. 17 Science.

Robots that can work in close, crowded quarters without tripping each other up may be especially good at digging through rubble for search-and-rescue missions, disaster cleanup or construction, says Justin Werfel, a collective behavior researcher at Harvard University who has designed insect-inspired robot swarms.

Daniel Goldman, a physicist at Georgia Tech in Atlanta, and colleagues pored over footage of about 30 fire ants digging tunnels during 12-hour stretches. “To our surprise, we found that there’s only about three to five ants doing anything” at a time, Goldman says. Although individual ants’ activity levels varied over time, about 30 percent of the ants did about 70 percent of the work in any given 12-hour period.

To investigate why fire ants divvy up work this way, Goldman’s team created computer simulations of two ant colonies digging tunnels. In one, the virtual ants mimicked the real insects’ unequal work split; in the other, all the ants pitched in equally. The colony with fewer heavy lifters was better at keeping tunnel traffic moving; in three hours, that colony dug a tunnel that was about three times longer than the group of ants that all did their fair share.

Goldman’s team then tested the fire ants’ teamwork strategy on autonomous robots. These robots trundled back and forth along a narrow track, scooping up plastic balls at one end and dumping them at the other. Programming the robots to do equal work is “not so bad when you have two or three,” Goldman says, “but when you get four in that little narrow tunnel, forget about it.” The four-bot fleet tended to get stuck in pileups. Programming the robots to share the workload unequally helped avoid these smashups and move material 35 percent faster, the researchers found.

J. Aguilar et al. Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation. Science. Vol. 361, August 17, 2018, p. 672.

https://www.sciencenews.org/article/what-robots-could-learn-fire-ants


An electronics repair company gives a compassionate farewell to mechanical pets, with a traditional ceremony held in a historic temple.

By James Burch
A traveler happening upon a funeral for robot dogs might be taken aback.

Is this a performance art statement about modern life? Is it a hoax? A practical joke?

But this is actually a religious ceremony, and the emotions expressed by the human participants are genuine.

A dog-shaped robot—as opposed to say, a dish on wheels with a built-in vacuum cleaner—represented a focus on entertainment and companionship. When Sony released the AIBO (short for “artificial intelligence robot”) in 1999, 3,000 units—the greater share of the first run—were sold to the Japanese market. At an initial cost of $3,000 in today’s money, those sold out in 20 minutes.

But AIBOs never became more than a niche product, and in 2006 Sony canceled production. In seven years, they’d sold 150,000 of the robots.

Some AIBO owners had already become deeply attached to their pet robots, though. And here is where the story takes an unexpected turn.

AIBOs aren’t like a remote-control car. They were designed to move in complex, fluid ways, with trainability and a simulated mischievous streak. (Meet Sophia, the robot that almost seems human.)

Over time, they would come to “know” their human companions, who grew attached to them as if they were real dogs. (Learn how playing games helped build the modern world.)

The AIBOs’ programs included both doggish behaviors, like tail-wagging, and humanlike actions, such as dancing, and—in later models—speech.

So when Sony announced in 2014 that they would no longer support updates to the aging robots, some AIBO owners heard a much more somber message: Their pet robot dogs would die. The community of devoted owners began sharing tips on providing care for their pets in the absence of official support.

Nobuyuki Norimatsu didn’t intend to create a cyberhospital. According to Nippon.com, the former Sony employee, who founded the repair company A-Fun in a Chiba Prefecture, a Tokyo suburb, simply felt a duty to stand by the company’s products. (Watch sunlight create a heart inside a Chiba Prefecture cave.)

And then came a request to repair an AIBO. Nippon.com reports that, at first, no one knew exactly what to do, but months of trial and error saw the robodog back on its feet. Soon, A-Fun had a steady demand for AIBO repairs—which could only be made by cannibalizing parts from other, defunct AIBOs.

Hiroshi Funabashi, A-Fun’s repairs supervisor, observes that the company’s clients describe their pets’ complaints in such terms as “aching joints.” Funabashi realized that they were not seeing a piece of electronic equipment, but a family member.

And Norimatsu came to regard the broken AIBOs his company received as “organ donors.” Out of respect for the owners’ emotional connection to the “deceased” devices, Norimatsu and his colleagues decided to hold funerals.

A-Fun approached Bungen Oi, head priest of Kōfuku-ji, a Buddhist temple in Chiba Prefecture’s city of Isumi. Oi agreed to take on the duty of honoring the sacrifice of donor AIBOs before their disassembly. In 2015, the centuries-old temple held its first robot funeral for 17 decommissioned AIBOs. Just as with the repairs, demand for funeral ceremonies quickly grew.

The most recent service, in April 2018, brought the total number of dearly departed AIBOs to about 800. Tags attached to the donor bodies record the dogs’ and owners’ names.

Services include chanting and the burning of incense, as they would for the human departed. A-Fun employees attend the closed ceremonies, serving as surrogates for the “families” of the pets, and pliers are placed before the robodogs in place of traditional offerings like fruit. Robots even recite Buddhist sutras, or scriptures. (Meet a master of Japanese Tea Ceremony.)

According to Head Priest Oi, honoring inanimate objects is consistent with Buddhist thought. Nippon.com quotes the priest: “Even though AIBO is a machine and doesn’t have feelings, it acts as a mirror for human emotions.” Speaking with videographer Kei Oumawatari, Oi cites a saying, “Everything has Buddha-nature.”

AIBOs and similar robots are especially popular among the elderly, and limited research hints that robots could potentially act like therapy animals—though attachment to machines could also be a symptom of loneliness, an increasing concern in Japan. (READ: Will a robot be your friend or steal your job?)

Sony has now introduced a new line of more advanced AIBOs, and although they are apparently not technologically compatible with their predecessors, it would seem they stand a good chance of finding similar popularity with those who can appreciate the soul of a machine.

Though AIBO funerals are closed to the public, travelers in Japan can at other times visit the Isumi’s historic Kōfuku-ji, one of several temples in the region including work by the master wood carver IHACHI. Isumi tourist info (Click on “Select Language” in the upper right for English.)

To learn about other personal robots, such as Paro, a therapeutic seal-bot, visit the permanent exhibit “Create your future” at Miraikan, the National Museum of Emerging Science and Innovation in Tokyo.

https://www.nationalgeographic.com/travel/destinations/asia/japan/in-japan–a-buddhist-funeral-service-for-robot-dogs/

Thanks to Kebmodee for bringing this to the It’s Interesting community.

One advantage humans have over robots is that we’re good at quickly passing on our knowledge to each other. A new system developed at MIT now allows anyone to coach robots through simple tasks and even lets them teach each other.

Typically, robots learn tasks through demonstrations by humans, or through hand-coded motion planning systems where a programmer specifies each of the required movements. But the former approach is not good at translating skills to new situations, and the latter is very time-consuming.

Humans, on the other hand, can typically demonstrate a simple task, like how to stack logs, to someone else just once before they pick it up, and that person can easily adapt that knowledge to new situations, say if they come across an odd-shaped log or the pile collapses.

In an attempt to mimic this kind of adaptable, one-shot learning, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) combined motion planning and learning through demonstration in an approach they’ve dubbed C-LEARN.

First, a human teaches the robot a series of basic motions using an interactive 3D model on a computer. Using the mouse to show it how to reach and grasp various objects in different positions helps the machine build up a library of possible actions.

The operator then shows the robot a single demonstration of a multistep task, and using its database of potential moves, it devises a motion plan to carry out the job at hand.

“This approach is actually very similar to how humans learn in terms of seeing how something’s done and connecting it to what we already know about the world,” says Claudia Pérez-D’Arpino, a PhD student who wrote a paper on C-LEARN with MIT Professor Julie Shah, in a press release.

“We can’t magically learn from a single demonstration, so we take new information and match it to previous knowledge about our environment.”

The robot successfully carried out tasks 87.5 percent of the time on its own, but when a human operator was allowed to correct minor errors in the interactive model before the robot carried out the task, the accuracy rose to 100 percent.

Most importantly, the robot could teach the skills it learned to another machine with a completely different configuration. The researchers tested C-LEARN on a new two-armed robot called Optimus that sits on a wheeled base and is designed for bomb disposal.

But in simulations, they were able to seamlessly transfer Optimus’ learned skills to CSAIL’s 6-foot-tall Atlas humanoid robot. They haven’t yet tested Atlas’ new skills in the real world, and they had to give Atlas some extra information on how to carry out tasks without falling over, but the demonstration shows that the approach can allow very different robots to learn from each other.

The research, which will be presented at the IEEE International Conference on Robotics and Automation in Singapore later this month, could have important implications for the large-scale roll-out of robot workers.

“Traditional programming of robots in real-world scenarios is difficult, tedious, and requires a lot of domain knowledge,” says Shah in the press release.

“It would be much more effective if we could train them more like how we train people: by giving them some basic knowledge and a single demonstration. This is an exciting step toward teaching robots to perform complex multi-arm and multi-step tasks necessary for assembly manufacturing and ship or aircraft maintenance.”

The MIT researchers aren’t the only people investigating the field of so-called transfer learning. The RoboEarth project and its spin-off RoboHow were both aimed at creating a shared language for robots and an online repository that would allow them to share their knowledge of how to carry out tasks over the web.

Google DeepMind has also been experimenting with ways to transfer knowledge from one machine to another, though in their case the aim is to help skills learned in simulations to be carried over into the real world.

A lot of their research involves deep reinforcement learning, in which robots learn how to carry out tasks in virtual environments through trial and error. But transferring this knowledge from highly-engineered simulations into the messy real world is not so simple.

So they have found a way for a model that has learned how to carry out a task in a simulation using deep reinforcement learning to transfer that knowledge to a so-called progressive neural network that controls a real-world robotic arm. This allows the system to take advantage of the accelerated learning possible in a simulation while still learning effectively in the real world.

These kinds of approaches make life easier for data scientists trying to build new models for AI and robots. As James Kobielus notes in InfoWorld, the approach “stands at the forefront of the data science community’s efforts to invent ‘master learning algorithms’ that automatically gain and apply fresh contextual knowledge through deep neural networks and other forms of AI.”

If you believe those who say we’re headed towards a technological singularity, you can bet transfer learning will be an important part of that process.

https://singularityhub.com/2017/05/26/these-robots-can-teach-other-robots-how-to-do-new-things/?utm_source=Singularity+Hub+Newsletter&utm_campaign=7c19f894b1-Hub_Daily_Newsletter&utm_medium=email&utm_term=0_f0cf60cdae-7c19f894b1-58158129

A viral video showing an army of little orange robots sorting out packages in a warehouse in eastern China is the latest example of how machines are increasingly taking over menial factory work on the mainland.

The behind-the-scenes footage of the self-charging robot army in a sorting centre of Chinese delivery powerhouse Shentong (STO) Express was shared on People’s Daily’s social media accounts on Sunday.

The video showed dozens of round orange Hikvision robots – each the size of a seat cushion – swivelling across the floor of the large warehouse in Hangzhou, Zhejiang province.

A worker was seen feeding each robot with a package before the machines carried the parcels away to different areas around the sorting centre, then flipping their lids to deposit them into chutes beneath the floor.

The robots identified the destination of each package by scanning a code on the parcel, thus minimising sorting mistakes, according to the video.

The machines can sort up to 200,000 packages a day and are self-charging, meaning they can operate around the clock.

An STO Express spokesman told the South China Morning Post on Monday that the robots had helped the company save half the costs it typically required to use human workers.

They also improved efficiency by around 30 per cent and maximised sorting accuracy, he said.

“We use these robots in two of our centres in Hangzhou right now,” the spokesman said. “We want to start using these across the country, especially in our bigger centres.”

Although the machines could run around the clock, they were presently used only for about six or seven hours each time from 6pm, he said.

Manufacturers across China have been increasingly replacing human workers with machines.

The output of industrial robots in the country grew 30.4 per cent last year.

In the country’s latest five-year plan, the central government set a target aiming for annual production of these robots to reach 100,000 by 2020.

Apple’s supplier Foxconn last year replaced 60,000 factory workers with robots, according to a Chinese government official in Kunshan, eastern Jiangsu province.

The Taiwanese smartphone maker has several factories across China.

http://www.scmp.com/news/china/society/article/2086662/chinese-firm-cuts-costs-hiring-army-robots-sort-out-200000

Thanks to Kebmodee for bringing this to the It’s Interesting community.

by Tom Simonite

Each of these trucks is the size of a small two-story house. None has a driver or anyone else on board.

Mining company Rio Tinto has 73 of these titans hauling iron ore 24 hours a day at four mines in Australia’s Mars-red northwest corner. At this one, known as West Angelas, the vehicles work alongside robotic rock drilling rigs. The company is also upgrading the locomotives that haul ore hundreds of miles to port—the upgrades will allow the trains to drive themselves, and be loaded and unloaded automatically.

Rio Tinto intends its automated operations in Australia to preview a more efficient future for all of its mines—one that will also reduce the need for human miners. The rising capabilities and falling costs of robotics technology are allowing mining and oil companies to reimagine the dirty, dangerous business of getting resources out of the ground.

BHP Billiton, the world’s largest mining company, is also deploying driverless trucks and drills on iron ore mines in Australia. Suncor, Canada’s largest oil company, has begun testing driverless trucks on oil sands fields in Alberta.

“In the last couple of years we can just do so much more in terms of the sophistication of automation,” says Herman Herman, director of the National Robotics Engineering Center at Carnegie Mellon University, in Pittsburgh. The center helped Caterpillar develop its autonomous haul truck. Mining company Fortescue Metals Group is putting them to work in its own iron ore mines. Herman says the technology can be deployed sooner for mining than other applications, such as transportation on public roads. “It’s easier to deploy because these environments are already highly regulated,” he says.

Rio Tinto uses driverless trucks provided by Japan’s Komatsu. They find their way around using precision GPS and look out for obstacles using radar and laser sensors.

Rob Atkinson, who leads productivity efforts at Rio Tinto, says the fleet and other automation projects are already paying off. The company’s driverless trucks have proven to be roughly 15 percent cheaper to run than vehicles with humans behind the wheel, says Atkinson—a significant saving since haulage is by far a mine’s largest operational cost. “We’re going to continue as aggressively as possible down this path,” he says.

Trucks that drive themselves can spend more time working because software doesn’t need to stop for shift changes or bathroom breaks. They are also more predictable in how they do things like pull up for loading. “All those places where you could lose a few seconds or minutes by not being consistent add up,” says Atkinson. They also improve safety, he says.

The driverless locomotives, due to be tested extensively next year and fully deployed by 2018, are expected to bring similar benefits. Atkinson also anticipates savings on train maintenance, because software can be more predictable and gentle than any human in how it uses brakes and other controls. Diggers and bulldozers could be next to be automated.

Herman at CMU expects all large mining companies to widen their use of automation in the coming years as robotics continues to improve. The recent, sizeable investments by auto and tech companies in driverless cars will help accelerate improvements in the price and performance of the sensors, software, and other technologies needed.

Herman says many mining companies are well placed to expand automation rapidly, because they have already invested in centralized control systems that use software to coördinate and monitor their equipment. Rio Tinto, for example, gave the job of overseeing its autonomous trucks to staff at the company’s control center in Perth, 750 miles to the south. The center already plans train movements and in the future will shift from sending orders to people to directing driverless locomotives.

Atkinson of Rio Tinto acknowledges that just like earlier technologies that boosted efficiency, those changes will tend to reduce staffing levels, even if some new jobs are created servicing and managing autonomous machines. “It’s something that we’ve got to carefully manage, but it’s a reality of modern day life,” he says. “We will remain a very significant employer.”

https://www.technologyreview.com/s/603170/mining-24-hours-a-day-with-robots/

Thanks to Kebmodee for bringing this to the It’s Interesting community.