January 17, 2014 06:26pm ETYour Robot Helper is On The Way Now It Can Learn From Its Friends I’ll be right with you sir, just after I put this cup away. This is a cup, right? Credit: garrettc. View full size image

This article was originally published at The Conversation. The publication contributed the article to LiveScience's Expert Voices: Op-Ed & Insights.

January is a time when many of us seek to better ourselves. We want to learn a new skill or improve an existing one. A network designed especially for robots, RoboEarth, is being tested in the Netherlands to help them with their attempts at self-improvement. Soon our mechanical friends will be able to swap tips on how to best care for us and learn about their worlds.

As demonstrated by Google’s recent purchase of robotics companies and Amazon’s automated warehouses, intelligent, autonomous service robots are starting to look commercially viable.

Service robots are machines which can perform tasks with or for humans in normal environments (rather than in controlled factory settings). Intelligent, autonomous service robots have some freedom about how they complete tasks and need to make decisions about how to act based on what they know and can sense.

There are robots that can make sandwiches, find objects in your home, do your washing and even assemble Ikea furniture.

Easy on the mayo, please. Sandwich-making robots

Learning from scratch every time

When building systems such as these, one of the major bottlenecks is providing the robot with the knowledge about the world it needs in order to perform its task. This knowledge is usually centred around the objects involved in a task: what they look like, how they can be picked up or where they can be found. Knowledge about space (maps of buildings and rooms) and action (how to change the world to achieve a particular end) is usually essential too.

But robots have no built-in knowledge about these kinds of things. Everything they need to know must be engineered into their software somehow, such as by using machine learning techniques then connecting the results of this training to symbols within the robot’s software to allow it to refer to the things in the world.

This knowledge engineering typically takes a huge amount of time for even a simple task and is usually limited in that the robot only ends up knowing about exactly the things you’ve taught it. For example, it might be able to recognise a box of Cornflakes, but not a box of Frosties, or perhaps not even a box of Cornflakes with different packaging.

This means that it is very difficult to just send a robot into a new environment, or ask it to perform a new task, without having a team of experts on hand to do this training. No-one can afford to ship a computer science PhD graduate with every robot so researchers around the world are looking at how robots can be equipped to quickly learn about a new environment when they are put in one.

Learning from robot friends

RoboEarth – a collaboration between universities and Philips – has developed an approach to this based on the ability to share knowledge over the internet.

The system has been likened to a social network or a Wikipedia for robots as it allows the knowledge created for one robot to be shared with another robot, anywhere else in the world, via a shared, web-accessible database. When one robot in Germany learns what a toaster is and how it works, it can upload that information into the network. A robot in Japan which has never used a toaster before can then log in and learn how to recognise one.

To enable robots with different bodies and sensors to learn from each other, RoboEarth has an abstraction layer which allows shared information to assume common capabilities across all platforms. This is much like how a desktop operating system like Windows allows the same software to run on many different types of computers.

To allow robots to easily find the knowledge they require, the contents of the RoboEarth database are structured via an ontology. This describes each entry using logic which can be queried automatically and relates connected entries. So an oven will be listed as a type of household appliance and a mars bar as a type of food.

The RoboEarth demonstration is just the start of what will become an increasing trend of intelligent, autonomous machines sharing knowledge over the internet. While there are limitations to the current demonstrators, in terms of how well shared knowledge transfers across different systems and environments, we can expect this field to progress as robots begin to hit the market. The commercial need for robots to be able to learn from their peers will drive progress.

In the future it is easy to imagine both the current open protocols of RoboEarth educating robots worldwide, as well as a commercial alternative, like an app store, where robots and their owners can buy professionally engineered knowledge off the shelf. This will be a significant step towards the day when your morning orange juice or coffee will be brought by a robot helper, or at least a step towards helping it to tell the difference between the two.

Nick Hawes receives funding from the European Commission and EPSRC. He is affiliated with the University of Birmingham.

This article was originally published at The Conversation. Read the original article. The views expressed are those of the author and do not necessarily reflect the views of the publisher. This version of the article was originally published on LiveScience.

可以向其朋友学习的机器人助手即将问世

Your机器??人助手是在路上现在可以借鉴其Friends 我马上跟你先生，就在我把这个杯子了。这是一个杯子，对不对？

这篇文章最初发表在对话。该刊物贡献了文章，以生活科学的专家声音：社论版和放大器;洞察.

月份是当我们许多人寻求超越自我的时候。我们要学习一门新技能或提升现有的。特别是对机器人设计的网络，RoboEarth，正在荷兰进行测试，以帮助他们在自我提升他们的企图。不久，我们的机械的朋友将能够在交换技巧如何最好地对我们的关心和了解他们的世界.

就证明了谷歌＆rsquo的;最近收购机器人公司和亚马逊＆rsquo的第; S自动化仓库，智能化，自主服务机器人开始寻找商业上可行的.

服务机器人是可以直接或间接为人类在正常的环境中（而不是控制出厂设置）执行任务的机器。智能化，自主服务机器人有一些关于他们完成任务以及如何需要就如何根据他们所知道的行动，并能感知的决策自由.

有机器人，可以做三明治，发现在你的家里对象，请你洗甚至组装宜家家具.

易·梅奥，请。三明治制作机器人

都从头

学习建筑时，如这些系统中，主要的瓶颈之一是提供有关需要，以执行其任务，世界知识的机器人。这方面的知识通常是围绕参与任务的对象：他们的样子，他们怎么可以捡到或在那里他们可以找到。知识空间与行动（建筑物和房间地图）（如何改变世界，以实现特定的结束）通常是必不可少的太.

但是机器人没有关于这些事情的内置知识。他们需要知道的一切都必须设计到他们的软件以某种方式，例如通过使用机器学习技术则本次培训的结果连接到机器人＆rsquo的文件中的符号;的软件，使其能够参考的东西在世界上.

这知识工程通常需要大量的时间，即使是一个简单的任务，通常是有限的，机器人只会结束后知道究竟的事情，你和rsquo的;已经教了吧。例如，它可能是能够识别框玉米片，但不是一个框Frosties的，或者甚至没有一个盒具有不同的包装的玉米片.

这意味着，这是很困难的只是发送一个机器人到一个新的环境，或要求它执行新的任务，而不必手头上的专家团队做这个训练。没有人能买得起船计算机科学博士研究生毕业与每一个机械手，以便在世界各地的研究人员正在研究机器人如何可以配备快速了解一个新的环境中放一个，当他们。

从机器人朋友学习

RoboEarth＆ndash的;大学和飞利浦＆ndash的之间的合作;已经开发出一种方法来此基础上通过互联网.

该系统已被??比喻为一个社交网络或维基百科机器人分享知识的能力，因为它允许一个机器人创造的知识与另一个机器人共享，任何地方在世界其他，通过共享，网络访问的数据库。当德国一个机器人学会什么烤面包机以及它是如何工作的，它可以上传信息到网络中。那么在日本的机器人这之前从未使用过烤面包机可以登录并学习如何承认一个.

为了使机器人与不同的机构和传感器互相学习，RoboEarth都有它允许共享的信息承担共同的一个抽象层能力跨越所有平台。这很像一个桌面操作系统如Windows如何允许同一软件在许多不同类型的计算机上运行.

为了让机器人能够很容易地找到他们所需要的知识，在RoboEarth数据库的内容通过本体的结构。本描述使用的逻辑可被自动查询和涉及连接条目的每个条目。因此，一个烤箱将其列为一类家电和火星吧作为一类食品.

的RoboEarth演示是会变成什么样的智能，自主机共享知识在互联网上有增加的趋势仅仅是开始。虽然有一些限制目前的示威者，在如何共同在不同的系统和环境中的知识转移方面，我们可以期待这一领域取得进展的机器人开始冲击市场。商业需要机器人能够从他们的同龄人将推动进步.

学习

在未来，不难想象这两个RoboEarth教育机器人在全世界的当前打开的协议，以及一个商业的替代，像一个应用程序商店，其中，机器人和它们的主人可以购买专业设计知识下架。这将是对当你早晨橙汁或咖啡将被带到一个机器人帮手，或者至少对帮助它的一个步骤，告诉两个.

尼克 - 霍伊斯得到了欧洲委员会资助的区别当天显著一步和EPSRC。他参加与伯明翰大学.

这篇文章最初发表在对话。阅读原创文章。表达的观点属于作者本人，并不一定反映出版者的看法。这个版的文章最初发表在生活科学。