Acquiring knowledge of object arrangements from human examples for household robots

Abstract

Robots are becoming ever more present in households, interacting more with humans. They are able to perform tasks in an accurate manner, e.g. manipulating objects. However, this manipulation often does not follow the human way to arrange objects. Therefore, robots require semantic knowledge about the environment for executing tasks and satisfying humans’ expectations. In this paper, we will introduce a breakfast table setting scenario where a robot acquires information from human demonstrations to arrange objects in a meaningful way. We will show how robots can obtain the necessary amount of knowledge to autonomously perform daily tasks.