Robots Learning from Experience

Software that enables robots to move objects about a room, building up ever-more knowledge about their environment, is an important step forward in artificial intelligence. Some objects can be moved, while others cannot. Balls can be placed on top of boxes, but boxes cannot be stably stacked on top of balls. A typical one-year-old child can discover this kind of information about its environment very quickly. But it is a massive challenge for a robot – a machine – to learn concepts such as ‘movability’ and ‘stability’, according to researchers at the Bonn-Rhein-Sieg University and members of the Xpero robotics research project team. The aim of the Xpero project was to develop a cognitive system for a robot that would enable it to explore the world around it and learn through physical experimentation. The first step was to create an algorithm that enabled the robot to discover its environment from data it received from its sensors. The Xpero researchers installed some very basic predefined knowledge into the robot based on logic. The robot believes that things are either true or false. The robot uses the data from its sensors as it moves about to test that knowledge. When the robot finds that an expectation is false it starts to experiment to find out why it is false and to correct its hypotheses. Picking out the important factors in the massive and continuous flow of data from the robot’s sensors created one challenge for the EU-funded Xpero project team. Finding a way for a logic-based system to deal with the concept of time was a second challenge.

Part of the Xpero team’s solution was to ignore some of the flow of data coming in every millisecond and instead to get the robot to compare snapshots of the situation after a few seconds. When an expectation proved false they also cut down the possible number of solutions by getting the robot to build a new hypothesis that kept the logic connectors from its old hypothesis, simply changing the variables. That drastically reduced the number of possible solutions. An important development from Xpero is the robot’s ability to build its knowledge base. In award-winning demonstrations, robots with the Xpero cognitive system on board have moved about, pushed and placed objects, learning all the time about their environment. In an exciting recent development the robot has started to use objects as tools. It has used one object to move or manipulate another object that it cannot reach directly. The Xpero project lays the first cornerstones for a technology that has the potential to become a key technology for the next generation of so-called service robots, which clean our houses and mow our lawns – replacing the rather dumb, pre-programmed devices on the market today. A robotics manufacturer is already planning to use parts of the Xpero platform in the edutainment market.

More information:

http://cordis.europa.eu/ictresults/index.cfm?section=news&tpl=article&BrowsingType=Features&ID=91421