Astronaut controls robot on Earth from the ISS

An astronaut aboard the International Space Station used an extraterrestrial remote control system on Friday to maneuver a robot rover at NASA's Ames Research Center in Silicon Valley.

In the test, Italian astronaut Luca Parmitano used the rover to deploy a simulated radio telescope antenna on the Ames Roverscape, a sandy and rocky simulation of the lunar landscape that's about the size of a football field.

Parmitano was controlling the rover from a Java application running on a Lenovo ThinkPad on the ISS. The rover, a four-wheeled robot called a K10, steadily moved around the Roverscape as it was commanded during the test. A team of NASA scientists kept watch on the test at Ames, but it was Parmitano in control all the time, they said.

"Our goal here really, overall, is to understand how humans and robots can really work well together," said Terry Fong, telerobotics program manager at NASA Ames. "And not just any kind of robot, we're really interested in remotely operated robots. In particular, we're looking at how can we use these robots to improve the way humans can live and work in space."

The test, one of a series, points to NASA's latest thinking about lunar and planetary exploration. Whereas the Apollo astronauts did everything themselves and the Mars Rover has done its work autonomously, NASA is looking to a future where astronauts control nearby robots to carry out tasks.

That can't be done easily from Earth because of the long time it takes for radio signals to travel the vast distance to neighboring planets. In the case of Mars, there's an eight-minute delay before a signal reaches the planet, and then an eight-minute return time for a confirmation signal.

So while Friday's test had an ISS astronaut controlling a rover in Silicon Valley, it simulated a future lunar mission with a spacecraft in an orbit between the moon and Earth.

"We've chosen a mission scenario that involves taking a robot to the far side of the moon and deploying a radio telescope to observe the early history of the universe, the so-called cosmic dawn," Fong said.

Scientists are eyeing the moon's far side as a location for a future radio telescope because the moon itself shields the location from radio interference being emitted from Earth. Radio and communications transmitters continuously blast out signals on the frequencies of interest to radio astronomers, so finding a spot with little radio noise is a challenge. After the moon, they estimate the next best location for low radio noise is beyond Jupiter.

In the test, the simulated radio telescope antenna was made of a thin, plastic film that was stored on a roll inside the rover's body. The rover drove to a pre-determined point and one end of the film would drop from the back. It then moved forward, unrolling the antenna onto the ground behind it as it drove.

"The future is going to be an astronaut or a series of astronauts in control of a fleet of rovers, either if you're on the surface of a planetary body like the moon or Mars or from orbit," said Jack Burns, a professor at the University of Colorado and director of the lunar university network for astrophysics research.

Internet traffic jams, meet your robot nemesis

On an 80-core computer at the Massachusetts Institute of Technology, scientists have built a tool that might make networks significantly faster just by coming up with better algorithms.

The system, called Remy, generates its own algorithms for implementing TCP (Transmission Control Protocol), the framework used to prevent congestion on most networks. The algorithms are different from anything human developers have written, and so far they seem to work much better, according to the researchers. On one simulated network, they doubled the throughput.

Remy is not designed to run on individual PCs and servers, but someday it may be used to develop better algorithms to run on those systems, said Hari Balakrishnan, the Fujitsu professor in Electrical Engineering and Computer Science at MIT. For now, it's churning out millions of possible algorithms and testing them against simulated networks to find the best possible one for a given objective.

IP (Internet Protocol) networks don't dictate how fast each attached computer sends out packets or whether they keep transmitting after the network has become congested. Instead, each system makes its own decisions using some implementation of the TCP framework. Each version of TCP uses its own algorithm to determine how best to act in different conditions.

These implementations of TCP have been refined many times over the past 30 years and sometimes fine-tuned for particular networks and applications. For example, a Web browser may put a priority on moving bits across the network quickly, while a VoIP application may call for less delay. Today, there are 30 to 50 "plausibly good" TCP schemes and five to eight that are commonly used, Balakrishnan said.

But up to now, those algorithms have all been developed by human engineers, he said. Remy could change that.

"The problem, on the face of it, is actually intractably hard for computers," Balakrishnan said. Because there are so many variables involved and network conditions constantly change, coming up with the most efficient algorithm requires more than "naive" brute-force computing, he said.

Figuring out how to share a network requires strategic choices not unlike those that cyclists have to make in bike races, such as whether to race ahead and take the lead or cooperate with another racer, said Balakrishnan's colleague, graduate student Keith Winstein.

"There's a lot of different computers, and they all want to let their users browse the Web, and yet they have to cooperate to share the network," Winstein said.

However, Remy can do things that human algorithm developers haven't been able to achieve, Balakrishnan said. For one thing, current TCP algorithms use only a handful of rules for how a computer should respond to performance issues. Those might include things like slowing the transmission rate when the percentage of dropped packets passes some threshold. Remy can create algorithms with more than 150 rules, according to the researchers.

To create a new algorithm using Remy, Balakrishnan and Winstein put in a set of requirements and then let Remy create candidates and try them against software that simulates a wide range of network conditions. The system uses elements of machine learning to determine which potential algorithm best does the job. As it tests the algorithms, Remy focuses on situations where a small change in network conditions can lead to a big change in performance, rather than on situations where the network is more predictable.

After about four to 12 hours, Remy delivers the best algorithm it's found. The results have been impressive, according to the researchers. In a test that simulated a fast wired network with consistent transmission rates across physical links, Remy's algorithms produced about twice the throughput of the most commonly used versions of TCP and cut delay by two-thirds, they said. On a simulation of Verizon's mobile data network, Remy's algorithms gave 20 percent to 30 percent better throughput and 25 percent to 40 percent lower delay.

But don't expect blazing page loads just yet. Balakrishnan and Winstein cautioned that Remy is still an academic research project.

For one thing, it hasn't yet been tested on the actual Internet. Though Remy's algorithms would probably work fairly well out there, it's hard to be sure because they were developed in simulations that didn't include all of the Internet's unknown variables, according to Balakrishnan. For example, it may be hard to tell how many people are active on a particular part of the Internet, he said.

If machine-developed TCP algorithms do end up going live, it will probably happen first on private networks. For example, companies such as Google already fine-tune TCP for the requirements of their own data centers, Balakrishnan said. Those kinds of companies might turn to a system like Remy to develop better ones.

But even if Remy never makes it into the real world, it may have a lot to teach the engineers who write TCP algorithms, Balakrishnan said. For example, Remy uses a different way of thinking about whether there is congestion than TCP does today, he said.

Though the researchers understand certain tools that Remy uses, they still want to figure out how that combination of tools can create such good algorithms.

"Empirically, they work very well," Winstein said. "We get higher throughput, lower delay and more fairness than in all the human designs to date. But we cannot explain why they work."

"At this point, our real aspiration is that other researchers and engineers pick it up and start using it as a tool," Balakrishnan said. "Even if the ultimate impact of our work is ... more about changing the way people think about the problem, for us, that is a huge win."

Foxconn to speed up 'robot army' deployment; 20,000 robots already in its factories

Manufacturing giant Foxconn Technology Group is on track with its goal to a create a "million robot army", and already has 20,000 robotic machines in its factories, said the company's CEO Terry Gou on Wednesday.

 

Workers' wages in China are rising, and so the company's research in robots and automation has to catch up, Gou said, while speaking at the company's annual shareholder's meeting in Taipei. "We have over 1 million workers. In the future we will add 1 million robotic workers," he said. "Our [human] workers will then become technicians and engineers."

 

Foxconn is the world's largest contract electronics maker and counts Apple, Microsoft and Sony as some of its clients. Many of its largest factories are in China, where the company employs 1.2 million people, but rising worker salaries are threatening to reduce company profits.

 

To offset labor costs and improve its manufacturing, Foxconn has already spent three years on developing robots, Gou said. These machines are specifically developed to assemble electronics such as mobile phones, but it will take some time for Foxconn to fully develop the technology, he added.

 

"It's a middle to long-term goal," Gou said. But already 20,000 robot arms and robotic tools are in use at the company's factories.

 

Robotics have long been used to manufacture cars and large electronics. But currently, human workers are still the best choice to put together small consumer gadgets, many of which contain complicated wiring and small sockets that are best handled with human hands, according to experts.

 

In addition, Foxconn's CEO said the company is prepared to expand its manufacturing in the U.S., but the move will depend on "economic factors." The company already has factories in Indianapolis and Houston, and employs thousands of workers in the country, according to Gou.

 

Last December, Foxconn customer Apple said it would manufacture one of its Mac lines in the U.S. by the end of next year. Soon after, Foxconn said it was considering growing its existing manufacturing base in the country.

 

The Taiwanese company is also exploring building factories in Indonesia, a country with significantly lower labor costs than the U.S. or China. One possible plan is for Foxconn to build electronics for the local market, which is home to 240 million people.

 

"Indonesia has great potential and its a great market for my company," Gou said. "Definitely we will put a lot of investment in Indonesia."

 

The company, however, is waiting for the nation's government to improve the regulations for its tech sector. Standards over electronics safety are so low that anyone can get away with selling shoddy mobile phones, said a Foxconn official in December.

 

"The direction is right, but we need to take time," Gou added. "We think in one or two years this will happen."