iSGTW is now Science Node Learn more about our evolution

  • Subscribe

Robots get their own Wikipedia to learn and share

Think of it: an intelligent network comprised of autonomous robots. No, not like the Terminator's self-aware computer system bent on destroying humanity, but a Wikipedia-like resource for robots to learn, and to share their newly found knowledge. It's called RoboEarth and it's being built by Swiss researchers.

If robots are ever to become useful, they have a lot to learn. "Today's robots don't know many of the things we take for granted: milk turns bad if it's not in the fridge. The milk bottle can break. The oven gets hot when it's turned on. We learn these and many more things about our world in our first years of life. But, although they seem so basic, today no robot has this basic knowledge," said Markus Waibel, from the Swiss Federal Institute of Technology(ETH)in Zurich.

Robot connected to Wikipedia-like RoboEarth serves a drink of water to a hospital patient
Robot connected to RoboEarth serves a drink of water to a hospital patient. Image courtesy Eindhoven/Angeline Swinkels.

RoboEarth will enable robots connected via its network to share information, learn and increase their overall memory. "It is not intended as a communication network. Rather, it will construct a knowledge base, much like Wikipedia," Waibel said.

The perception of artificial intelligence has changed over the years, Waibel said.

"Initially we thought logic was the highest form of intelligence. Today we know that there is much more to building an artificial intelligence than logical reasoning.

"A network like RoboEarth will likely exacerbate current ethical, moral, and legal challenges. However, for now these issues are dwarfed by the technological challenges."

The reason is that the more varied robots are the more difficult sharing knowledge between them becomes. "We humans excel at dealing with unstructured information, however, for a robot even a fairly structured knowledge resource like Wikipedia is too ambiguous and incomplete. For example, Wikipedia lists 23 alternative meanings for the word robot," Waibel said.

Structuring data categories to help robots learn faster

"Ultimately, an Internet for robots will have to cover a lot more knowledge than Wikipedia and need to be far more structured." Waible and his colleagues RoboEarth scientists are currently using KnowRob, a taxonomic structure to help robots learn faster. This will help robots learn about data categories that include everything from geography and basic physics to manipulation tasks and offline learning.

Currently, the European Commission FP7 funded project is using a single server to host the RoboEarth database. "However, the software architecture is built on a cloud computing framework that is highly scalable," said Waibel.

RoboEarth's scientists want robotic systems to benefit from the experience of other robots in other environments, paving the way for rapid advances in machine cognition, behavior, and eventually, better human and machine interaction. "While science fiction writers have imagined artificial intelligences in Terminator and Space Odyssey series, I think those analogies are flawed. RoboEarth is about building a knowledge base, and while it may include intelligent web services or a robot app store, it will probably be about as self-aware as Wikipedia," said Waibel.

The release of an open source version of RoboEarth is scheduled for July 2011.

Join the conversation

Do you have story ideas or something to contribute?
Let us know!

Copyright © 2015 Science Node ™  |  Privacy Notice  |  Sitemap

Disclaimer: While Science Node ™ does its best to provide complete and up-to-date information, it does not warrant that the information is error-free and disclaims all liability with respect to results from the use of the information.


We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on” containing a link back to the original article.
  4. The easiest way to get the article on your site is to embed the code below.