ALOOF will enable robots to tap into the ever-growing amount of knowledge available on the Web, by learning from there about the meaning of previously unseen objects, expressed in a form that makes them applicable when acting in situated environments. By searching the Web, robots will be able to learn about new objects, their specific properties, where they might be stored and so forth. To achieve this, robots need a mechanism for translating between the representations used in their real-world experience and those on the Web.
The goal of ALOOF is to significantly advance the ability of today’s autonomous systems to adapt to ever changing, dynamic real world environments by enabling them to learn about the meaning of objects from resources accessible through the Web.
In ALOOF we will explicitly focus on objects and the knowledge gaps a service robot will encounter about them.
The fundamental contribution of ALOOF will be to enable robots to translate between the representations they use in their situated experience and those on the Web.