From Affordances to Situated Affordances in Robotics - Why Context is Important

We propose situated affordances as an extension to the well known concept of affordances. Situated affordances extend affordances by taking the environmental context, in which an object is embedded, into account. We argue that the extended concept allows the learning of qualitatively more complex tasks. In this paper we report the conceptual result of ongoing work in which a cognitive robotic architecture is developed that finally should be able to learn complex real world tasks. The purpose of this paper is to communicate the proposed conceptual idea to the scientific community, to get in touch with other researchers and to foster the interchange between roboticists, psychologists and associated researchers who are concerned with the learning of complex tasks in robots.