Learning affordance for semantic robots using ontology approach

Abstract

Learning affordance is very important for autonomous robots to know what the necessary actions should be performed to complete a given task with its abilities. However, itpsilas difficult to identify and apply affordances in practice for robots. In order for a robot to get benefits from this concept, this paper proposes ontology approach based affordance concept for ubiquitous robots. The goal of this affordance-based ontology effort is to develop and begin to populate a neutral knowledge representation capturing relevant information about robots capabilities and what the environment afford to assist human life in ubiquitous robots environment. We propose a new method to dasiateachpsila robot learn objects and context affordances using ontology approach for semantic robots in ubiquitous robots space.