Latest in Robotics news thread

[ScienceRocks]

Boeing patents a drone that turns into a submarine
By Eric Mack - August 18, 2015 1 Picture

Boeing has been given a patent for a new kind of amphibious drone that's like something straight out of a classic spy movie. The aeronautics giant has a novel design for an unmanned aerial drone that can spontaneously convert into an unmanned submarine and go for a dive.

 

[ScienceRocks]

US Navy will have squadron of large robotic submarines by 2020 and mass production in 2025

The Navy will building prototype large robotic submarines in 2015-2016 and testing in 2018. According to the Navy's ISR Capabilities Division, LDUUV will reach initial operating capability as a squadron by 2020 and full rate production by 2025. The US Navy has released requirements for its long duration large robotic submarine. (LDUUV -...

 

[ScienceRocks]

The economic myth of robotics and the robot job-ocalypse

Arnold Schwarzenegger’s Terminator was science fiction — but so, too, is the idea that robots and software algorithms are guzzling jobs faster than they can be created. There is an astonishing mismatch between our fear of automation and the reality so far.
How can this be? The highways of Silicon Valley are sprinkled with self-driving cars. Visit the cinema, the supermarket or the bank and the most prominent staff you will see are the security guards, who are presumably there to prevent you stealing valuable machines. Your computer once contented itself with correcting your spelling; now it will translate your prose into Mandarin. Given all this, surely the robots must have stolen a job or two by now?
Of course, the answer is that automation has been destroying particular jobs in particular industries for a long time, which is why most westerners who weave clothes or cultivate and harvest crops by hand do so for fun. In the past that process made us richer.
The worry now is that, with computers making jobs redundant faster than we can generate new ones, the result is widespread unemployment, leaving a privileged class of robot-owning rentiers and highly paid workers with robot-compatible skills.
This idea is superficially plausible: we are surrounded by cheap, powerful computers; many people have lost their jobs in the past decade; and inequality has risen in the past 30 years.
But the theory can be put to a very simple test: how fast is productivity growing? The usual measure of productivity is output per hour worked — by a human. Robots can produce economic output without any hours of human labour at all, so a sudden onslaught of robot workers should cause a sudden acceleration in productivity.
Instead, productivity has been disappointing. In the US, labour productivity growth averaged an impressive 2.8 per cent per year from 1948 to 1973. The result was mass affluence rather than mass joblessness. Productivity then slumped for a generation and perked up in the late 1990s but has now sagged again. The picture is little better in the UK, where labour productivity is notoriously low compared with the other G7 leading economies, and it has been falling further behind since 2007.

 

[ScienceRocks]

Atlas, a Humanoid Robot, Takes a Walk in the Woods

Scientists trying to build a better robot are encouraged by the steps, however tentative, of a humanoid named Atlas.
In a video shown recently by Atlas’s makers, it is hard to miss the human in the humanoid as the 6-foot-2 machine takes a casual, careful stroll through the woods. It walks like a crouched limbo contestant (who perhaps imbibed one too many piña coladas), shuffles through a wooded area, tethered by a power cord, and then breaks into a more confident, foot-slapping walk when it reaches flat ground — much as a person would. Scientists hope to make an untethered version soon.

 

[ScienceRocks]

Biophysicists take small step in quest for 'robot scientist'

27 August 2015


Biophysicists have taken another small step forward in the quest for an automated method to infer models describing a system's dynamics - a so-called robot scientist. Nature Communications published the finding - a practical algorithm for inferring laws of nature from time-series data of dynamical systems.

"Our algorithm is a small step," says Ilya Nemenman, lead author of the study and a professor of physics and biology at Emory University. "It could be described as a toy version of a robot scientist, but even so it may have practical applications. For the first time, we've taught a computer how to efficiently search for the laws that underlie arbitrary, natural dynamical systems, including complex, non-linear biological systems."
Nemenman's co-author on the paper is Bryan Daniels, a biophysicist at the University of Wisconsin.




http://www.spacedail...entist_999.html

 

[ScienceRocks]

Deep Learning achieves human-level performance on language task

Quote

The task is called simlex-999. Basically, it's about telling whether words are "similar" or merely "related". For example, "coffee" and "cup" are "related", obviously; but they are not "similar" -- "coffee" is a beverage, and "cup" is something that holds liquid. On the other hand, "car" and "bus" are similar -- both are modes of transportation; both have drivers; both have passengers; both ride on roads; etc.


Quote

This version differs from the previous one with the inclusion
of Appendix A, which contains details about new higher
dimensional embeddings we have released. These embeddings
achieve human-level performance on SL999 and WS353.





The phone keeps ringing...

 

[ScienceRocks]

Fully automated lettuce factory to open in Japan

If you imagine lettuce as a crop planted in a field and tended by farmers, you're behind the times.
Kyoto-based vegetable factory operator Spread Co. said it will begin construction of what it calls a fully automated large-scale lettuce factory in spring 2016, which will be able to produce 30,000 heads of lettuce per day with "a push of a button."
The company isn't quite finished with the factory's development. According to Spread, there are six stages to growing a lettuce at a factory: seeding, germination, raising the seedlings, transplanting them into a larger bed, raising the vegetable and harvesting. The company said it is still working on a machine that can handle the seeding process. And it still requires human eyes to confirm germination. Beyond that, every process is automated, it says.
Stacker cranes are to carry the lettuce seedlings and hand them over to robots which will take care of transplanting them. Once fully grown, they will be harvested and delivered automatically to the factory's packaging line. The automated process will not only handle the lettuce but also control the temperature, humidity, level of carbon dioxide, sterilization of water and lighting hours, the company said.
Spread has seven years of experience in growing lettuce in its factories, with the produce being sold in 2,000 stores in Japan. While the lettuce is sold for about the same price as that grown in regular farms today, the company hopes to bring down costs. It says the factory lettuce tastes the same as lettuce grown outdoors.
Shipments from the fully automated lettuce factory are expected to begin in summer 2017

 

[ScienceRocks]

Robots Lay Three Times as Many Bricks as Construction Workers

Construction workers on some sites are getting new, non-union help. SAM – short for semi-automated mason – is a robotic bricklayer being used to increase productivity as it works with human masons.
In this human-robot team, the robot is responsible for the more rote tasks: picking up bricks, applying mortar, and placing them in their designated location. A human handles the more nuanced activities, like setting up the worksite, laying bricks in tricky areas, such as corners, and handling aesthetic details, like cleaning up excess mortar.
Even in completing repetitive tasks, SAM still has to be fairly adaptable. It’s able to complete precise and level work while mounted on a scaffold that sways slightly in the wind. The robot can correct for the differences between theoretical building specifications and what’s actually on site, says Scott Peters, cofounder of Construction Robotics, a company based in Victor, New York, that designed SAM as its debut product.

 

[ScienceRocks]

DJI adds intelligent flight modes to Phantom 3 family

Last month, DJI released the Phantom 3 Standard drone, which slotted in below the Phantom 3 Advanced and Phantom 3 Professional in the company's lineup. At the time, DJI promised compatibility with a series of intelligent flight modes would be forthcoming in a software update and the company has now delivered on that promise.

 

[ScienceRocks]

Deep Learning Machine Teaches Itself Chess in 72 Hours, Plays at International Master Level

Having trained Giraffe, the final step is to test it and here the results make for interesting reading. Lai tested his machine on a standard database called the Strategic Test Suite, which consists of 1,500 positions that are chosen to test an engine’s ability to recognize different strategic ideas. “For example, one theme tests the understanding of control of open files, another tests the understanding of how bishop and knight’s values change relative to each other in different situations, and yet another tests the understanding of center control,” he says.

The results of this test are scored out of 15,000.
Lai uses this to test the machine at various stages during its training. As the bootstrapping process begins, Giraffe quickly reaches a score of 6,000 and eventually peaks at 9,700 after only 72 hours. Lai says that matches the best chess engines in the world.
“[That] is remarkable because their evaluation functions are all carefully hand-designed behemoths with hundreds of parameters that have been tuned both manually and automatically over several years, and many of them have been worked on by human grandmasters,” he adds.
....
“Unlike most chess engines in existence today, Giraffe derives its playing strength not from being able to see very far ahead, but from being able to evaluate tricky positions accurately, and understanding complicated positional concepts that are intuitive to humans, but have been elusive to chess engines for a long time,” says Lai. “This is especially important in the opening and end game phases, where it plays exceptionally well.”
And this is only the start. Lai says it should be straightforward to apply the same approach to other games. One that stands out is the traditional Chinese game of Go, where humans still hold an impressive advantage over their silicon competitors. Perhaps Lai could have a crack at that next.

 

[ScienceRocks]

System learns to distinguish words' phonetic components, without human annotation of training data

Every language has its own collection of phonemes, or the basic phonetic units from which spoken words are composed. Depending on how you count, English has somewhere between 35 and 45. Knowing a language's phonemes can make it much easier for automated systems to learn to interpret speech.

In the 2015 volume of Transactions of the Association for Computational Linguistics, MIT researchers describe a new machine-learning system that, like several systems before it, can learn to distinguish spoken words. But unlike its predecessors, it can also learn to distinguish lower-level phonetic units, such as syllables and phonemes.
As such, it could aid in the development of speech-processing systems for languages that are not widely spoken and don't have the benefit of decades of linguistic research on their phonetic systems. It could also help make speech-processing systems more portable, since information about lower-level phonetic units could help iron out distinctions between different speakers' pronunciations.
Unlike the machine-learning systems that led to, say, the speech recognition algorithms on today's smartphones, the MIT researchers' system is unsupervised, which means it acts directly on raw speech files: It doesn't depend on the laborious hand-annotation of its training data by human experts. So it could prove much easier to extend to new sets of training data and new languages.
Finally, the system could offer some insights into human speech acquisition. "When children learn a language, they don't learn how to write first," says Chia-ying Lee, who completed her PhD in computer science and engineering at MIT last year and is first author on the paper. "They just learn the language directly from speech. By looking at patterns, they can figure out the structures of language. That's pretty much what our paper tries to do."
Lee is joined on the paper by her former thesis advisor, Jim Glass, a senior research scientist at the Computer Science and Artificial Intelligence Laboratory and head of the Spoken Language Systems Group, and Timothy O'Donnell, a postdoc in the MIT Department of Brain and Cognitive Sciences.

 

[ScienceRocks]

Fujitsu Achieves 96.7% Recognition Rate for Handwritten Chinese Characters Using Deep Learning AI That Mimics the Human Brain

First time ever to be more accurate than human recognition, according to conference

Quote

Fujitsu R&D Center Co., Ltd. and Fujitsu Laboratories Ltd. (collectively Fujitsu) today announced the development of the world's first handwriting recognition technology by utilizing AI technology modeled on human brain processes to surpass a human equivalent recognition rate of 96.7%, that was established at a conference.

Fujitsu had previously achieved top-level accuracy in this field, as demonstrated by taking first place, with a recognition rate of 94.8%, at a handwritten Chinese character recognition contest(1) held at the International Conference on Document Analysis and Recognition (ICDAR), a top-level conference in the document image processing field. However, in order to further increase recognition accuracy, a new mechanism for studying the diversity of character deformations was required.

Now, with a focus on a hierarchical model of expanded connections between neurons, a model based on the human brain which grasps the features of the characters, Fujitsu has developed a technology to automatically create numerous patterns of character deformation from the character's base pattern, thereby "training" this hierarchical neural model. Using this method, Fujitsu has achieved an accuracy rate of 96.7%, surpassing the human equivalent recognition rate of 96.1% for handwritten Chinese characters(2).

Fujitsu expects that this technology will enable further automation of computer input and recognition.

Ordinarily, while humans can easily recognize media such as characters, images and sounds, for computers this recognition is much more difficult, due to both the many variations in shape, brightness and so on of the object to be recognized, as well as the existence of similar objects. This has become a central problem in artificial intelligence research.

Fujitsu has decades of experience in character recognition, with commercialized technologies used in such areas as Japan's finance and insurance fields for Japanese language, as well as a Chinese character recognition technology used by the Chinese government for 800 million handwritten census forms. Fujitsu started research using artificial intelligence based on deep learning for character recognition in 2010. In 2013, the character recognition technology developed on the basis of this artificial intelligence took first place (recognition rate of 94.8%) at a handwritten Chinese character recognition contest held at a top-level international contest in the document image processing field, achieving the highest accuracy in the field.

 

[GHook93]

That's what I've been trying to tell folks.. Low skilled sweat labor is pretty much dead. Those robot hamburglars are gonna have a ball flirting with the customers during the break.

But they'll always be jobs TEACHING robots to assemble customized or new menu items.

We have a MONSTROUS societal shift about to take place... As large and disruptive as the industrial revolution.. And all we want to talk about is how evil rich folks are responsible for taking all the jobs away.. We're being badly misled..

Do you really think it will only be low skilled jobs? Smart machines will be able to do accounting better the a person! A lawyer can only process and remember so much regulations and case law and computer can disseminate the entire NY penal code in seconds.

Will we need pilots, soldier, police etc? They will probably get replaced.

Teachers? Stock Brokers?

The list will go on and on. There will always be jobs, but fewer of them and the ever growing population.


Sent from my iPhone using Tapatalk

 

[flacaltenn]

That's what I've been trying to tell folks.. Low skilled sweat labor is pretty much dead. Those robot hamburglars are gonna have a ball flirting with the customers during the break.

But they'll always be jobs TEACHING robots to assemble customized or new menu items.

We have a MONSTROUS societal shift about to take place... As large and disruptive as the industrial revolution.. And all we want to talk about is how evil rich folks are responsible for taking all the jobs away.. We're being badly misled..

Do you really think it will only be low skilled jobs? Smart machines will be able to do accounting better the a person! A lawyer can only process and remember so much regulations and case law and computer can disseminate the entire NY penal code in seconds.

Will we need pilots, soldier, police etc? They will probably get replaced.

Teachers? Stock Brokers?

The list will go on and on. There will always be jobs, but fewer of them and the ever growing population.


Sent from my iPhone using Tapatalk

There's SOME pressure from Art. Intelligence on all of those jobs you mentioned. But take an accountant. He's ALREADY automated largely. But the part that cannot be replaced right now -- is the interview to get to the FACTS of the accounting. Has to be familiar with too many varying types of jobs and income and it is necessary to to have follow-up questions in a conversational manner.

JUDGEMENT is hard to teach a machine when it involves situational awareness. Situational awareness requires many forms of sentient inputs. As in the military, law enforcement, etc. The scenario is more like ALL of these professions will have to rise in education and awareness of how to USE these automations without serious mistakes and errors.

And more importantly -- we cannot allow any further dumbing down or lowered expectations on REQUIRED education K-12.. AND we will need specializations for EVERY "semi-skilled" profession. Much like a greatly expanded Trade School platform post High School..

 

[ScienceRocks]

Bosch is developing a farming robot that can distinguish crops from weed and pics them out mechanically

Quote

Bosch-funded start-up company Deepfield Robotics is the latest company to develop a field vehicle that can distinguish weeds from crops and neatly fish them out.
The technology, named Bonirob, claims that it will make plant breeding more efficient and reduce the environmental impact of crop farming.
Bonirob, which is the size of a small car, can monitor how well new crop varieties grow, whether they are resistant to pests and how much fertiliser and water they need.
Currently, this is a painstaking manual process done by plant scientists in a laboratory.

 

[ScienceRocks]

University of Tehran unveils Surena III humanoid robot

• Ben Coxworth
• November 19, 2015
• 2 PICTURES

The likes of Asimo, Valkyrie and ATLAS better make some room, as there's a new humanoid robot on the block – and it looks not unlike the Gort bot from the original The Day the Earth Stood Still. It's the third version of the University of Tehran's Surena robot, and it was unveiled this Monday.

 

[ScienceRocks]

DJI's agriculture drone takes to the air down on the farm

• Nick Lavars
• November 29, 2015
• 3 PICTURES

They may not capture the imagination in the same way as say, drones that deliver items in 30 minutes or shoot stunning 4K video, but drones stand to have a big impact on agriculture. Crop dusting and seeding has been carried out by aircraft for more than a century, but we are starting to see their autonomous and agile younger cousins emerge as highly suitable tools for the job. This is of course not lost on the world's biggest drone maker DJI, which has just a launched a drone for farmers that can be programmed to cover acres of farmland in pesticides every hour.

 

[ScienceRocks]

Drone attachment scans disaster zones for breathing and heartbeats

• Nick Lavars
• November 29, 2015
• 2 PICTURES

Getting drones into the air to aid in search and rescue missions is becoming one of the technologies more promising applications, with infrared cameras and even artificial intelligence offering valuable new tools in combing areas for humans and objects. But one company is looking to add yet another layer of sophistication to robotic rescue teams, launching a drone-attachment that can detect the heartbeats and breathing of people trapped under rubble.

 

[ScienceRocks]

Golf ball-gathering Ball Picker robot is like a Roomba for the range

• Nick Lavars
• December 6, 2015
• 6 PICTURES

Roaming around a driving range retrieving the endless scattering of golf balls is a pretty tall order for staff, especially when you consider the bays full of weekend hackers taking aim at their caged buggies. But one company is looking to give golfers a smaller moving target to aim at. The Ball Picker robot autonomously scoots around sucking up golf balls and returns them to a ball dispenser to be teed up once again.

 

[AdvancingTime]

Interesting topic! I have also written several articles about how robots will change our culture going forward. For example, we should all try to be grownups and face the fact that robots have uses other than moving things around the factory floor. Sex-bots could make our human spouses obsolete, someone had to say it. Robots are being looked at to fulfill a variety of needs, some of these uses are less distasteful than the killing machines the military seeks.

The integration of robots into our culture will bring about massive changes in society and could cause many people to totally rethink how the define the term "relationship". The article below titled, "Sex-bots Could Make Spouse Obsolete" explores some of the ramifications and advancements being made in related industries.

Advancing Time: Sex-bots Could Make Spouse Obsolete